From c4cd6784e564d438407ba97565c94b49cb6bfb45 Mon Sep 17 00:00:00 2001 From: Szymon Rodziewicz Date: Sat, 17 Jan 2026 18:56:21 +0100 Subject: [PATCH 1/3] Reorganize and adjust core modules before beta release --- .../computenode/cyfra/core/Allocation.scala | 11 +++ .../cyfra/core/GBufferRegion.scala | 3 +- .../io/computenode/cyfra/core/GCodec.scala | 10 ++ .../io/computenode/cyfra/core/GProgram.scala | 3 + .../scala/io/computenode/cyfra/dsl/Dsl.scala | 26 +++++- .../cyfra/dsl/algebra/ScalarAlgebra.scala | 3 + .../cyfra/dsl/algebra/VectorAlgebra.scala | 3 + cyfra-foton/src/main/scala/foton/Api.scala | 93 ------------------- .../computenode/cyfra/foton}/GFunction.scala | 6 +- .../cyfra/foton/ImageUtility.scala | 20 ++++ .../animation/AnimatedFunctionRenderer.scala | 14 ++- .../foton/animation/AnimationRenderer.scala | 26 ++++-- .../cyfra/foton/rt/ImageRtRenderer.scala | 4 +- .../cyfra/foton/rt/RtRenderer.scala | 8 +- .../rt/animation/AnimationRtRenderer.scala | 2 +- .../cyfra/runtime/VkAllocation.scala | 33 +++++-- .../computenode/cyfra/runtime/VkBinding.scala | 17 +--- 17 files changed, 142 insertions(+), 140 deletions(-) delete mode 100644 cyfra-foton/src/main/scala/foton/Api.scala rename {cyfra-core/src/main/scala/io/computenode/cyfra/core/archive => cyfra-foton/src/main/scala/io/computenode/cyfra/foton}/GFunction.scala (95%) create mode 100644 cyfra-foton/src/main/scala/io/computenode/cyfra/foton/ImageUtility.scala diff --git a/cyfra-core/src/main/scala/io/computenode/cyfra/core/Allocation.scala b/cyfra-core/src/main/scala/io/computenode/cyfra/core/Allocation.scala index cdc0be06..469621c9 100644 --- a/cyfra-core/src/main/scala/io/computenode/cyfra/core/Allocation.scala +++ b/cyfra-core/src/main/scala/io/computenode/cyfra/core/Allocation.scala @@ -8,6 +8,7 @@ import io.computenode.cyfra.dsl.struct.{GStruct, GStructSchema} import izumi.reflect.Tag import java.nio.ByteBuffer +import scala.reflect.ClassTag trait Allocation: def submitLayout[L: Layout](layout: L): Unit @@ -17,14 +18,24 @@ trait Allocation: def write(bb: ByteBuffer, offset: Int = 0): Unit + extension [T <: Value: {Tag, FromExpr}](buffer: GBinding[T]) + + def readArray[ST: ClassTag](arr: Array[ST], offset: Int = 0)(using GCodec[T, ST]): Array[ST] + + def writeArray[ST: ClassTag](arr: Array[ST], offset: Int = 0)(using GCodec[T, ST]): Unit + extension [Params, EL: Layout, RL: Layout](execution: GExecution[Params, EL, RL]) def execute(params: Params, layout: EL): RL extension (buffers: GBuffer.type) def apply[T <: Value: {Tag, FromExpr}](length: Int): GBuffer[T] + def apply[ST: ClassTag, T <: Value: {Tag, FromExpr}](scalaArray: Array[ST])(using GCodec[T, ST]): GBuffer[T] + def apply[T <: Value: {Tag, FromExpr}](buff: ByteBuffer): GBuffer[T] extension (buffers: GUniform.type) def apply[T <: GStruct[T]: {Tag, FromExpr, GStructSchema}](buff: ByteBuffer): GUniform[T] + def apply[ST: ClassTag, T <: GStruct[T]: {Tag, FromExpr, GStructSchema}](value: ST)(using GCodec[T, ST]): GUniform[T] + def apply[T <: GStruct[T]: {Tag, FromExpr, GStructSchema}](): GUniform[T] diff --git a/cyfra-core/src/main/scala/io/computenode/cyfra/core/GBufferRegion.scala b/cyfra-core/src/main/scala/io/computenode/cyfra/core/GBufferRegion.scala index ab773752..103e7520 100644 --- a/cyfra-core/src/main/scala/io/computenode/cyfra/core/GBufferRegion.scala +++ b/cyfra-core/src/main/scala/io/computenode/cyfra/core/GBufferRegion.scala @@ -41,7 +41,8 @@ object GBufferRegion: Some(((f.asInstanceOf[Allocation => Any => Any], req.resAllocLayout.asInstanceOf[Layout[Any]]), req)) val initAlloc = init(using allocation).tap(allocation.submitLayout) - val bodyAlloc = steps.foldLeft[Any](initAlloc): (acc, step) => + + val bodyAlloc = steps.reverse.foldLeft[Any](initAlloc): (acc, step) => step._1(allocation)(acc).tap(allocation.submitLayout(_)(using step._2)) onDone(using allocation)(bodyAlloc.asInstanceOf[ResAlloc]) diff --git a/cyfra-core/src/main/scala/io/computenode/cyfra/core/GCodec.scala b/cyfra-core/src/main/scala/io/computenode/cyfra/core/GCodec.scala index 9d4d4bb9..4048e498 100644 --- a/cyfra-core/src/main/scala/io/computenode/cyfra/core/GCodec.scala +++ b/cyfra-core/src/main/scala/io/computenode/cyfra/core/GCodec.scala @@ -19,6 +19,16 @@ trait GCodec[CyfraType <: Value: {FromExpr, Tag}, ScalaType: ClassTag]: object GCodec: + def toByteBuffer[CyfraType <: Value: {FromExpr, Tag}, ScalaType: ClassTag](inBuf: ByteBuffer, arr: Array[ScalaType])(using + gc: GCodec[CyfraType, ScalaType], + ): ByteBuffer = + gc.toByteBuffer(inBuf, arr) + + def fromByteBuffer[CyfraType <: Value: {FromExpr, Tag}, ScalaType: ClassTag](outBuf: ByteBuffer, arr: Array[ScalaType])(using + gc: GCodec[CyfraType, ScalaType], + ): Array[ScalaType] = + gc.fromByteBuffer(outBuf, arr) + def totalStride(gs: GStructSchema[?]): Int = gs.fields .map: case (_, fromExpr, t) if t <:< gs.gStructTag => diff --git a/cyfra-core/src/main/scala/io/computenode/cyfra/core/GProgram.scala b/cyfra-core/src/main/scala/io/computenode/cyfra/core/GProgram.scala index 9f9639df..0a62f5b2 100644 --- a/cyfra-core/src/main/scala/io/computenode/cyfra/core/GProgram.scala +++ b/cyfra-core/src/main/scala/io/computenode/cyfra/core/GProgram.scala @@ -36,6 +36,9 @@ object GProgram: )(body: L => GIO[?]): GProgram[Params, L] = new GioProgram[Params, L](body, s => layout(using s), dispatch, workgroupSize) + def static[Params, L: Layout](layout: InitProgramLayout ?=> Params => L, dispatchSize: Params => Int)(body: L => GIO[?]): GProgram[Params, L] = + GioProgram.apply(body, s => layout(using s), (l, p) => StaticDispatch((dispatchSize(p) + 127) / 128, 1, 1), (128, 1, 1)) + def fromSpirvFile[Params, L: Layout]( layout: InitProgramLayout ?=> Params => L, dispatch: (L, Params) => ProgramDispatch, diff --git a/cyfra-dsl/src/main/scala/io/computenode/cyfra/dsl/Dsl.scala b/cyfra-dsl/src/main/scala/io/computenode/cyfra/dsl/Dsl.scala index 3ad78773..d357ca7f 100644 --- a/cyfra-dsl/src/main/scala/io/computenode/cyfra/dsl/Dsl.scala +++ b/cyfra-dsl/src/main/scala/io/computenode/cyfra/dsl/Dsl.scala @@ -1,10 +1,34 @@ package io.computenode.cyfra.dsl // The most basic elements of the Cyfra DSL - +// Core types export io.computenode.cyfra.dsl.Value.* export io.computenode.cyfra.dsl.Expression.* +// Algebra +export io.computenode.cyfra.dsl.algebra.VectorAlgebra export io.computenode.cyfra.dsl.algebra.VectorAlgebra.{*, given} export io.computenode.cyfra.dsl.algebra.ScalarAlgebra.{*, given} +// Control flow export io.computenode.cyfra.dsl.control.When.* +export io.computenode.cyfra.dsl.control.Pure.pure +// Library functions export io.computenode.cyfra.dsl.library.Functions.* +export io.computenode.cyfra.dsl.library.Math3D.* +export io.computenode.cyfra.dsl.library.Color.* +export io.computenode.cyfra.dsl.library.Color.InterpolationThemes.* +export io.computenode.cyfra.dsl.library.Random.* +// Bindings +export io.computenode.cyfra.dsl.binding.GBuffer +export io.computenode.cyfra.dsl.binding.GUniform +// Collections +export io.computenode.cyfra.dsl.collections.GSeq +export io.computenode.cyfra.dsl.collections.GArray +export io.computenode.cyfra.dsl.collections.GArray2D +// Structs +export io.computenode.cyfra.dsl.struct.GStruct +export io.computenode.cyfra.dsl.struct.GStruct.given +export io.computenode.cyfra.dsl.struct.GStructSchema +// GPU IO +export io.computenode.cyfra.dsl.gio.GIO +// Macros +export io.computenode.cyfra.dsl.macros.Source diff --git a/cyfra-dsl/src/main/scala/io/computenode/cyfra/dsl/algebra/ScalarAlgebra.scala b/cyfra-dsl/src/main/scala/io/computenode/cyfra/dsl/algebra/ScalarAlgebra.scala index 92cbe6ae..475b936e 100644 --- a/cyfra-dsl/src/main/scala/io/computenode/cyfra/dsl/algebra/ScalarAlgebra.scala +++ b/cyfra-dsl/src/main/scala/io/computenode/cyfra/dsl/algebra/ScalarAlgebra.scala @@ -78,12 +78,15 @@ object ScalarAlgebra: def equal(a: T, b: T)(using Source): GBoolean = GBoolean(Equal(a, b)) + def notEqual(a: T, b: T)(using Source): GBoolean = GBoolean(Not(equal(a, b))) + extension [T <: Scalar: {Comparable, Tag}](a: T) inline def >(b: T)(using Source): GBoolean = summon[Comparable[T]].greaterThan(a, b) inline def <(b: T)(using Source): GBoolean = summon[Comparable[T]].lessThan(a, b) inline def >=(b: T)(using Source): GBoolean = summon[Comparable[T]].greaterThanEqual(a, b) inline def <=(b: T)(using Source): GBoolean = summon[Comparable[T]].lessThanEqual(a, b) inline def ===(b: T)(using Source): GBoolean = summon[Comparable[T]].equal(a, b) + inline def !==(b: T)(using Source): GBoolean = summon[Comparable[T]].notEqual(a, b) case class Epsilon(eps: Float) diff --git a/cyfra-dsl/src/main/scala/io/computenode/cyfra/dsl/algebra/VectorAlgebra.scala b/cyfra-dsl/src/main/scala/io/computenode/cyfra/dsl/algebra/VectorAlgebra.scala index 1f82a539..7908f63f 100644 --- a/cyfra-dsl/src/main/scala/io/computenode/cyfra/dsl/algebra/VectorAlgebra.scala +++ b/cyfra-dsl/src/main/scala/io/computenode/cyfra/dsl/algebra/VectorAlgebra.scala @@ -66,6 +66,9 @@ object VectorAlgebra: def vec4(x: FloatOrFloat32, y: FloatOrFloat32, z: FloatOrFloat32, w: FloatOrFloat32)(using Source): Vec4[Float32] = Vec4(ComposeVec4(toFloat32(x), toFloat32(y), toFloat32(z), toFloat32(w))) + def vec4(v3: Vec3[Float32], w: FloatOrFloat32)(using Source): Vec4[Float32] = + Vec4(ComposeVec4(toFloat32(v3.x), toFloat32(v3.y), toFloat32(v3.z), toFloat32(w))) + def vec3(x: FloatOrFloat32, y: FloatOrFloat32, z: FloatOrFloat32)(using Source): Vec3[Float32] = Vec3(ComposeVec3(toFloat32(x), toFloat32(y), toFloat32(z))) diff --git a/cyfra-foton/src/main/scala/foton/Api.scala b/cyfra-foton/src/main/scala/foton/Api.scala deleted file mode 100644 index 36d5bf50..00000000 --- a/cyfra-foton/src/main/scala/foton/Api.scala +++ /dev/null @@ -1,93 +0,0 @@ -package foton - -import io.computenode.cyfra.dsl.Value.* -import io.computenode.cyfra.dsl.library.{Color, Math3D} -import io.computenode.cyfra.utility.ImageUtility -import io.computenode.cyfra.foton.animation.AnimationRenderer -import io.computenode.cyfra.foton.animation.AnimationRenderer.{Parameters, Scene} -import io.computenode.cyfra.utility.Units.Milliseconds - -import java.nio.file.{Path, Paths} -import scala.concurrent.duration.DurationInt -import scala.concurrent.Await - -export io.computenode.cyfra.dsl.algebra.ScalarAlgebra.{*, given} -export io.computenode.cyfra.dsl.algebra.VectorAlgebra.{*, given} -export Color.* -export Math3D.{rotate, lessThan} - -/** Define function to be drawn - */ - -//private[foton] val connection = new VscodeConnection("localhost", 3000) -//private[foton] inline def outputPath(using f: sourcecode.FileName) = -// val filename = Path.of(summon[sourcecode.File].value).getFileName.toString -// Paths.get(s".cyfra/out/$filename.png").toAbsolutePath -// -//val Width = 1024 -//val WidthU = Width: UInt32 -//val Height = 1024 -//val HeightU = Height: UInt32 -// -//private[foton] enum RenderingStep(val step: Int, val stepName: String): -// case CompilingShader extends RenderingStep(1, "Compiling shader") -// case Rendering extends RenderingStep(2, "Rendering") -// -//private[foton] val renderingSteps = RenderingStep.values.length -// -//extension [A, B](a: A) -// infix def |>(f: A => B): B = f(a) -// -//object RenderingStep: -// def toMessage(step: RenderingStep) = RenderingMessage(step.step, renderingSteps, step.stepName) -// -//sealed trait RenderSettings -// -//case class RenderAsImage() extends RenderSettings -//case class RenderAsVideo(frames: Int, duration: Milliseconds) -// -//inline def f(fn: (Float32, Float32) => RGB)(using f: sourcecode.File, settings: RenderSettings = RenderAsImage()) = -// connection.send(RenderingStep.toMessage(RenderingStep.CompilingShader)) -// -// given GContext = new GContext -// settings match -// case RenderAsImage() => -// -// -// val gpuFunction: GArray2DFunction[Empty, Vec4[Float32], Vec4[Float32]] = GArray2DFunction(Width, Height, { -// case (_, (x, y), _) => -// val u = x.asFloat / WidthU.asFloat -// val v = y.asFloat / HeightU.asFloat -// val res = fn(u, v) -// (res.x, res.y, res.z, 1f) -// }) -// -// val data = Vec4FloatMem(Array.fill(Width * Height)((0f,0f,0f,0f))) -// connection.send(RenderingStep.toMessage(RenderingStep.Rendering)) -// -// val result = Await.result(data.map(gpuFunction), 30.seconds) -// ImageUtility.renderToImage(result, Width, Height, outputPath) -// connection.send(RenderedMessage(outputPath.toString)) -// -// case RenderAsVideo(frames, duration) => -// connection.send(RenderingStep.toMessage(RenderingStep.Rendering)) -// val scene = new Scene: -// def duration = duration -// -// val AnimationRenderer = new AnimationRenderer[Scene, GArray2DFunction[Empty, Vec4[Float32], Vec4[Float32]]](new Parameters: -// def width = Width -// def height = Height -// def framesPerSecond = 30 -// ): -// protected def renderFrame(scene: Empty, time: Float32, fn: GArray2DFunction[Empty, Vec4[Float32], Vec4[Float32]]): Array[RGBA] = -// val data = Vec4FloatMem(Array.fill(Width * Height)((0f,0f,0f,0f))) -// Await.result(data.map(fn), 30.seconds) -// -// protected def renderFunction(scene: Empty): GArray2DFunction[Empty, Vec4[Float32], Vec4[Float32]] = -// GArray2DFunction(Width, Height, { -// case (_, (x, y), _) => -// val u = x.asFloat / WidthU.asFloat -// val v = y.asFloat / HeightU.asFloat -// val res = fn(u, v) -// (res.x, res.y, res.z, 1f) -// }) diff --git a/cyfra-core/src/main/scala/io/computenode/cyfra/core/archive/GFunction.scala b/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/GFunction.scala similarity index 95% rename from cyfra-core/src/main/scala/io/computenode/cyfra/core/archive/GFunction.scala rename to cyfra-foton/src/main/scala/io/computenode/cyfra/foton/GFunction.scala index 180da5ae..b1dc7761 100644 --- a/cyfra-core/src/main/scala/io/computenode/cyfra/core/archive/GFunction.scala +++ b/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/GFunction.scala @@ -1,10 +1,10 @@ -package io.computenode.cyfra.core.archive +package io.computenode.cyfra.foton import io.computenode.cyfra.core.{CyfraRuntime, GBufferRegion, GCodec, GProgram} import io.computenode.cyfra.core.GBufferRegion.* import io.computenode.cyfra.core.GProgram.StaticDispatch -import io.computenode.cyfra.core.archive.GFunction -import io.computenode.cyfra.core.archive.GFunction.{GFunctionLayout, GFunctionParams} +import io.computenode.cyfra.foton.GFunction +import io.computenode.cyfra.foton.GFunction.{GFunctionLayout, GFunctionParams} import io.computenode.cyfra.core.layout.Layout import io.computenode.cyfra.dsl.Value.* import io.computenode.cyfra.dsl.binding.{GBuffer, GUniform} diff --git a/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/ImageUtility.scala b/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/ImageUtility.scala new file mode 100644 index 00000000..ad55f359 --- /dev/null +++ b/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/ImageUtility.scala @@ -0,0 +1,20 @@ +package io.computenode.cyfra.foton + +import java.awt.image.BufferedImage +import java.io.File +import java.nio.file.Path +import javax.imageio.ImageIO + +object ImageUtility: + def renderToImage(arr: Array[(Float, Float, Float, Float)], n: Int, location: Path): Unit = renderToImage(arr, n, n, location) + def renderToImage(arr: Array[(Float, Float, Float, Float)], w: Int, h: Int, location: Path): Unit = + val image = new BufferedImage(w, h, BufferedImage.TYPE_INT_RGB) + for y <- 0 until h do + for x <- 0 until w do + val (r, g, b, _) = arr(y * w + x) + def clip(f: Float) = Math.min(1.0f, Math.max(0.0f, f)) + val (iR, iG, iB) = ((clip(r) * 255).toInt, (clip(g) * 255).toInt, (clip(b) * 255).toInt) + image.setRGB(x, y, (iR << 16) | (iG << 8) | iB) + + val outputFile = location.toFile + ImageIO.write(image, "png", outputFile) diff --git a/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/animation/AnimatedFunctionRenderer.scala b/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/animation/AnimatedFunctionRenderer.scala index 49a5feed..b3a64ef5 100644 --- a/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/animation/AnimatedFunctionRenderer.scala +++ b/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/animation/AnimatedFunctionRenderer.scala @@ -7,7 +7,7 @@ import io.computenode.cyfra.dsl.struct.GStruct import io.computenode.cyfra.dsl.{*, given} import io.computenode.cyfra.foton.animation.AnimatedFunctionRenderer.{AnimationIteration, RenderFn} import io.computenode.cyfra.foton.animation.AnimationFunctions.AnimationInstant -import io.computenode.cyfra.core.archive.GFunction +import io.computenode.cyfra.foton.GFunction import io.computenode.cyfra.runtime.VkCyfraRuntime import scala.concurrent.ExecutionContext @@ -16,13 +16,14 @@ import scala.concurrent.ExecutionContext.Implicits class AnimatedFunctionRenderer(params: AnimatedFunctionRenderer.Parameters) extends AnimationRenderer[AnimatedFunction, AnimatedFunctionRenderer.RenderFn](params): - given CyfraRuntime = new VkCyfraRuntime() + private val runtime = new VkCyfraRuntime() + given CyfraRuntime = runtime given ExecutionContext = Implicits.global - override protected def renderFrame(scene: AnimatedFunction, time: Float32, fn: RenderFn): Array[fRGBA] = - val mem = Array.fill(params.width * params.height)((0.5f, 0.5f, 0.5f, 0.5f)) - fn.run(mem, AnimationIteration(time)) + val inputBuffer: Array[fRGBA] = Array.fill(params.width * params.height)((0.5f, 0.5f, 0.5f, 0.5f)) + java.util.Arrays.fill(inputBuffer.asInstanceOf[Array[Object]], (0.5f, 0.5f, 0.5f, 0.5f)) + fn.run(inputBuffer, AnimationIteration(time)) override protected def renderFunction(scene: AnimatedFunction): RenderFn = GFunction.from2D(params.width): @@ -33,6 +34,9 @@ class AnimatedFunctionRenderer(params: AnimatedFunctionRenderer.Parameters) val uv = (x, y) scene.fn(AnimatedFunction.FunctionArguments(lastFrame, lastColor, uv))(using AnimationInstant(time)) + /** Close the runtime to release GPU resources */ + override def close(): Unit = runtime.close() + object AnimatedFunctionRenderer: type RenderFn = GFunction[AnimationIteration, Vec4[Float32], Vec4[Float32]] case class AnimationIteration(time: Float32) extends GStruct[AnimationIteration] diff --git a/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/animation/AnimationRenderer.scala b/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/animation/AnimationRenderer.scala index 015be533..36048b87 100644 --- a/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/animation/AnimationRenderer.scala +++ b/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/animation/AnimationRenderer.scala @@ -3,8 +3,8 @@ package io.computenode.cyfra.foton.animation import io.computenode.cyfra import io.computenode.cyfra.dsl.Value.* import io.computenode.cyfra.dsl.{*, given} -import io.computenode.cyfra.core.archive.GFunction -import io.computenode.cyfra.utility.ImageUtility +import io.computenode.cyfra.foton.GFunction +import io.computenode.cyfra.foton.ImageUtility import io.computenode.cyfra.utility.Units.Milliseconds import io.computenode.cyfra.utility.Utility.timed @@ -16,14 +16,22 @@ trait AnimationRenderer[S <: AnimationRenderer.Scene, F <: GFunction[?, Vec4[Flo def renderFramesToDir(scene: S, destinationPath: Path): Unit = destinationPath.toFile.mkdirs() - val images = renderFrames(scene) + val function = renderFunction(scene) val totalFrames = Math.ceil(scene.duration / msPerFrame).toInt - val requiredDigits = Math.ceil(Math.log10(totalFrames)).toInt - images.zipWithIndex.foreach: - case (image, i) => - val frameFormatted = i.toString.reverse.padTo(requiredDigits, '0').reverse.mkString - val destionationFile = destinationPath.resolve(s"frame$frameFormatted.png") - ImageUtility.renderToImage(image, params.width, params.height, destionationFile) + val requiredDigits = Math.max(1, Math.ceil(Math.log10(totalFrames)).toInt) + try + for frame <- 0 until totalFrames do + val time = frame * msPerFrame + val image = timed(s"Animated frame $frame/$totalFrames"): + renderFrame(scene, time, function) + val frameFormatted = frame.toString.reverse.padTo(requiredDigits, '0').reverse.mkString + val destinationFile = destinationPath.resolve(s"frame$frameFormatted.png") + ImageUtility.renderToImage(image, params.width, params.height, destinationFile) + finally + close() + + /** Override to clean up resources after rendering */ + def close(): Unit = () def renderFrames(scene: S): LazyList[Array[fRGBA]] = val function = renderFunction(scene) diff --git a/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/rt/ImageRtRenderer.scala b/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/rt/ImageRtRenderer.scala index 3ad661dc..0206e71e 100644 --- a/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/rt/ImageRtRenderer.scala +++ b/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/rt/ImageRtRenderer.scala @@ -7,9 +7,9 @@ import io.computenode.cyfra.dsl.Value.* import io.computenode.cyfra.dsl.struct.GStruct import io.computenode.cyfra.dsl.{*, given} import io.computenode.cyfra.foton.rt.ImageRtRenderer.RaytracingIteration -import io.computenode.cyfra.core.archive.GFunction +import io.computenode.cyfra.foton.GFunction import io.computenode.cyfra.runtime.VkCyfraRuntime -import io.computenode.cyfra.utility.ImageUtility +import io.computenode.cyfra.foton.ImageUtility import io.computenode.cyfra.utility.Utility.timed import java.nio.file.Path diff --git a/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/rt/RtRenderer.scala b/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/rt/RtRenderer.scala index de38af62..0e26f09f 100644 --- a/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/rt/RtRenderer.scala +++ b/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/rt/RtRenderer.scala @@ -1,14 +1,8 @@ package io.computenode.cyfra.foton.rt import io.computenode.cyfra -import io.computenode.cyfra.dsl.Value.* -import io.computenode.cyfra.dsl.collections.{GArray2D, GSeq} -import io.computenode.cyfra.dsl.control.Pure.pure -import io.computenode.cyfra.dsl.library.Color.* -import io.computenode.cyfra.dsl.library.Math3D.* -import io.computenode.cyfra.dsl.library.Random -import io.computenode.cyfra.dsl.struct.GStruct import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.dsl.library.Random import io.computenode.cyfra.foton.rt.RtRenderer.RayHitInfo import scala.concurrent.ExecutionContext diff --git a/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/rt/animation/AnimationRtRenderer.scala b/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/rt/animation/AnimationRtRenderer.scala index 19ee393b..5f411888 100644 --- a/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/rt/animation/AnimationRtRenderer.scala +++ b/cyfra-foton/src/main/scala/io/computenode/cyfra/foton/rt/animation/AnimationRtRenderer.scala @@ -8,7 +8,7 @@ import io.computenode.cyfra.dsl.{*, given} import io.computenode.cyfra.foton.animation.AnimationRenderer import io.computenode.cyfra.foton.rt.RtRenderer import io.computenode.cyfra.foton.rt.animation.AnimationRtRenderer.RaytracingIteration -import io.computenode.cyfra.core.archive.GFunction +import io.computenode.cyfra.foton.GFunction import io.computenode.cyfra.runtime.VkCyfraRuntime class AnimationRtRenderer(params: AnimationRtRenderer.Parameters) diff --git a/cyfra-runtime/src/main/scala/io/computenode/cyfra/runtime/VkAllocation.scala b/cyfra-runtime/src/main/scala/io/computenode/cyfra/runtime/VkAllocation.scala index 3c43f07c..691a10ca 100644 --- a/cyfra-runtime/src/main/scala/io/computenode/cyfra/runtime/VkAllocation.scala +++ b/cyfra-runtime/src/main/scala/io/computenode/cyfra/runtime/VkAllocation.scala @@ -3,11 +3,7 @@ package io.computenode.cyfra.runtime import io.computenode.cyfra.core.layout.Layout import io.computenode.cyfra.core.{Allocation, GExecution, GProgram} import io.computenode.cyfra.core.SpirvProgram -import io.computenode.cyfra.dsl.Expression.ConstInt32 -import io.computenode.cyfra.dsl.Value -import io.computenode.cyfra.dsl.Value.FromExpr -import io.computenode.cyfra.dsl.binding.{GBinding, GBuffer, GUniform} -import io.computenode.cyfra.dsl.struct.{GStruct, GStructSchema} +import io.computenode.cyfra.dsl.* import io.computenode.cyfra.runtime.VkAllocation.getUnderlying import io.computenode.cyfra.spirv.SpirvTypes.typeStride import io.computenode.cyfra.vulkan.command.CommandPool @@ -21,11 +17,14 @@ import org.lwjgl.system.MemoryUtil import org.lwjgl.vulkan.{VK10, VkCommandBuffer, VkCommandBufferBeginInfo, VkDependencyInfo, VkMemoryBarrier2} import org.lwjgl.vulkan.VK13.* import org.lwjgl.vulkan.VK10.* - import java.nio.ByteBuffer import scala.collection.mutable import scala.util.Try import scala.util.chaining.* +import io.computenode.cyfra.dsl.binding.{GBinding, GBuffer, GUniform} +import io.computenode.cyfra.spirv.compilers.SpirvProgramCompiler.totalStride +import scala.reflect.ClassTag +import io.computenode.cyfra.core.GCodec class VkAllocation(val commandPool: CommandPool.Reset, executionHandler: ExecutionHandler)(using Allocator, Device) extends Allocation: given VkAllocation = this @@ -69,10 +68,27 @@ class VkAllocation(val commandPool: CommandPool.Reset, executionHandler: Executi binding.execution = Left(pe) case _ => throw new IllegalArgumentException(s"Tried to write to non-VkBinding $buffer") + extension [T <: Value: {Tag, FromExpr}](buffer: GBinding[T]) + + def writeArray[ST: ClassTag](arr: Array[ST], offset: Int = 0)(using GCodec[T, ST]): Unit = + val bb = BufferUtils.createByteBuffer(arr.size * typeStride(summon[Tag[T]])) + buffer.write(bb, 0) + GCodec.toByteBuffer[T, ST](bb, arr) + + def readArray[ST: ClassTag](arr: Array[ST], offset: Int = 0)(using GCodec[T, ST]): Array[ST] = + val bb = BufferUtils.createByteBuffer(arr.size * typeStride(summon[Tag[T]])) + buffer.read(bb, 0) + GCodec.fromByteBuffer[T, ST](bb, arr) + extension (buffers: GBuffer.type) def apply[T <: Value: {Tag, FromExpr}](length: Int): GBuffer[T] = VkBuffer[T](length).tap(bindings += _) + def apply[ST: ClassTag, T <: Value: {Tag, FromExpr}](scalaArray: Array[ST])(using GCodec[T, ST]): GBuffer[T] = + val bb = BufferUtils.createByteBuffer(scalaArray.size * typeStride(summon[Tag[T]])) + GCodec.toByteBuffer[T, ST](bb, scalaArray) + GBuffer[T](bb) + def apply[T <: Value: {Tag, FromExpr}](buff: ByteBuffer): GBuffer[T] = val sizeOfT = typeStride(summon[Tag[T]]) val length = buff.capacity() / sizeOfT @@ -84,6 +100,11 @@ class VkAllocation(val commandPool: CommandPool.Reset, executionHandler: Executi def apply[T <: GStruct[?]: {Tag, FromExpr, GStructSchema}](buff: ByteBuffer): GUniform[T] = GUniform[T]().tap(_.write(buff)) + def apply[ST: ClassTag, T <: GStruct[?]: {Tag, FromExpr, GStructSchema}](value: ST)(using GCodec[T, ST]): GUniform[T] = + val bb = BufferUtils.createByteBuffer(totalStride(summon[GStructSchema[T]])) + GCodec.toByteBuffer[T, ST](bb, Array(value)) + GUniform[T](bb) + def apply[T <: GStruct[?]: {Tag, FromExpr, GStructSchema}](): GUniform[T] = VkUniform[T]().tap(bindings += _) diff --git a/cyfra-runtime/src/main/scala/io/computenode/cyfra/runtime/VkBinding.scala b/cyfra-runtime/src/main/scala/io/computenode/cyfra/runtime/VkBinding.scala index 800379b9..1cdcd83d 100644 --- a/cyfra-runtime/src/main/scala/io/computenode/cyfra/runtime/VkBinding.scala +++ b/cyfra-runtime/src/main/scala/io/computenode/cyfra/runtime/VkBinding.scala @@ -1,12 +1,7 @@ package io.computenode.cyfra.runtime -import io.computenode.cyfra.dsl.Value -import io.computenode.cyfra.dsl.Value.FromExpr -import io.computenode.cyfra.spirv.SpirvTypes.typeStride +import io.computenode.cyfra.dsl.* import izumi.reflect.Tag -import io.computenode.cyfra.dsl.Value -import io.computenode.cyfra.dsl.Value.FromExpr -import io.computenode.cyfra.dsl.binding.{GBinding, GBuffer} import io.computenode.cyfra.vulkan.memory.{Allocator, Buffer} import io.computenode.cyfra.vulkan.core.Queue import io.computenode.cyfra.vulkan.core.Device @@ -14,15 +9,12 @@ import izumi.reflect.Tag import io.computenode.cyfra.spirv.SpirvTypes.typeStride import org.lwjgl.vulkan.VK10 import org.lwjgl.vulkan.VK10.{VK_BUFFER_USAGE_STORAGE_BUFFER_BIT, VK_BUFFER_USAGE_TRANSFER_DST_BIT, VK_BUFFER_USAGE_TRANSFER_SRC_BIT} -import io.computenode.cyfra.dsl.Value -import io.computenode.cyfra.dsl.Value.FromExpr -import io.computenode.cyfra.dsl.binding.GUniform -import io.computenode.cyfra.dsl.struct.{GStruct, GStructSchema} +import io.computenode.cyfra.spirv.compilers.SpirvProgramCompiler.totalStride import io.computenode.cyfra.vulkan.memory.{Allocator, Buffer} import izumi.reflect.Tag import org.lwjgl.vulkan.VK10 import org.lwjgl.vulkan.VK10.* - +import io.computenode.cyfra.dsl.binding.{GBinding, GBuffer, GUniform} import scala.collection.mutable import scala.util.chaining.given @@ -65,6 +57,7 @@ object VkUniform: VK_BUFFER_USAGE_INDIRECT_BUFFER_BIT def apply[T <: GStruct[_]: {Tag, FromExpr, GStructSchema}]()(using Allocator): VkUniform[T] = - val sizeOfT = typeStride(summon[Tag[T]]) + val schema = summon[GStructSchema[T]] + val sizeOfT = totalStride(schema) val buffer = new Buffer.DeviceBuffer(sizeOfT, UsageFlags) new VkUniform[T](buffer) From 42392f9d66e1ad2b94e059dbe6c534de2101852f Mon Sep 17 00:00:00 2001 From: Szymon Rodziewicz Date: Sat, 17 Jan 2026 18:58:16 +0100 Subject: [PATCH 2/3] Prepare examples (navier-stokes, analytics pipeline, small ones) and high-level dsl (fs2) for beta release --- build.sbt | 32 +- cyfra-analytics/IMPLEMENTATION.md | 168 ++++++ cyfra-analytics/README.md | 189 +++++++ cyfra-analytics/REFACTORING_SUMMARY.md | 195 +++++++ cyfra-analytics/src/main/resources/log4j2.xml | 13 + .../endpoints/SegmentationEndpoints.scala | 107 ++++ .../analytics/gpu/GpuAnalyticsPipeline.scala | 118 +++++ .../analytics/model/CentroidsUpdate.scala | 18 + .../cyfra/analytics/model/Domain.scala | 74 +++ .../repository/CentroidsRepository.scala | 12 + .../CustomerProfileRepository.scala | 18 + .../CustomerSegmentRepository.scala | 14 + .../InMemoryCentroidsRepository.scala | 129 +++++ .../InMemoryProfileRepository.scala | 34 ++ .../InMemorySegmentRepository.scala | 42 ++ .../analytics/server/SegmentationServer.scala | 71 +++ .../service/DataGenerationService.scala | 69 +++ .../service/FeatureExtractionService.scala | 261 ++++++++++ .../service/SegmentationService.scala | 168 ++++++ .../analytics/viz/ClusteringAnimation.scala | 156 ++++++ .../cyfra/analytics/LargeScaleE2ETest.scala | 271 ++++++++++ .../analytics/SegmentationEndpointsTest.scala | 87 ++++ .../analytics/SegmentationServiceTest.scala | 68 +++ cyfra-analytics/test-api.ps1 | 69 +++ cyfra-analytics/test-api.sh | 60 +++ .../compilers/SpirvProgramCompiler.scala | 8 +- .../cyfra/e2e/RuntimeEnduranceTest.scala | 7 +- .../cyfra/e2e/SpirvRuntimeEnduranceTest.scala | 5 - .../cyfra/e2e/dsl/ArithmeticsE2eTest.scala | 6 +- .../cyfra/e2e/dsl/FunctionsE2eTest.scala | 5 +- .../cyfra/e2e/dsl/GStructE2eTest.scala | 7 +- .../cyfra/e2e/dsl/GseqE2eTest.scala | 6 +- .../cyfra/e2e/dsl/WhenE2eTest.scala | 5 +- .../cyfra/e2e/fs2interop/Fs2Tests.scala | 5 +- .../cyfra/e2e/juliaset/JuliaSet.scala | 15 +- .../cyfra/samples/TestingStuff.scala | 4 - .../samples/examples/GFunctionExamples.scala | 213 ++++++++ .../samples/examples/GProgramExamples.scala | 247 +++++++++ .../cyfra/samples/foton/AnimatedJulia.scala | 3 - .../samples/foton/AnimatedRaytrace.scala | 1 - .../cyfra/samples/slides/4random.scala | 9 +- cyfra-fluids/src/main/resources/log4j2.xml | 16 + .../fluids/runner/FullFluidSimulation.scala | 481 ++++++++++++++++++ .../cyfra/fluids/solver/FluidParameters.scala | 59 +++ .../cyfra/fluids/solver/FluidState.scala | 43 ++ .../solver/programs/AdvectionProgram.scala | 64 +++ .../solver/programs/BoundaryProgram.scala | 53 ++ .../solver/programs/DiffusionProgram.scala | 63 +++ .../programs/DissipativeBoundaryProgram.scala | 112 ++++ .../solver/programs/ForcesProgram.scala | 41 ++ .../programs/FreeSlipBoundaryProgram.scala | 104 ++++ .../programs/NeumannBoundaryProgram.scala | 72 +++ .../programs/OutflowBoundaryProgram.scala | 120 +++++ .../solver/programs/ProjectionProgram.scala | 185 +++++++ .../programs/SourceInjectionProgram.scala | 122 +++++ .../VorticityConfinementProgram.scala | 152 ++++++ .../fluids/solver/utils/FieldUtils.scala | 400 +++++++++++++++ .../cyfra/fluids/solver/utils/GridUtils.scala | 127 +++++ .../fluids/solver/utils/ObstacleUtils.scala | 63 +++ .../cyfra/fluids/visualization/Camera3D.scala | 45 ++ .../fluids/visualization/FluidColorMap.scala | 76 +++ .../visualization/RayMarchRenderer.scala | 347 +++++++++++++ cyfra-fluids/src/test/resources/log4j2.xml | 16 + .../fluids/solver/AdvectionProgramTest.scala | 123 +++++ .../fluids/solver/BoundaryProgramTest.scala | 107 ++++ .../fluids/solver/DiffusionProgramTest.scala | 109 ++++ .../fluids/solver/ForcesProgramTest.scala | 104 ++++ .../fluids/solver/ProjectionProgramTest.scala | 215 ++++++++ .../cyfra/fs2interop/GCluster.scala | 320 ++++++++++++ .../computenode/cyfra/fs2interop/GPipe.scala | 41 ++ .../cyfra/utility/ImageUtility.scala | 20 - 71 files changed, 6710 insertions(+), 79 deletions(-) create mode 100644 cyfra-analytics/IMPLEMENTATION.md create mode 100644 cyfra-analytics/README.md create mode 100644 cyfra-analytics/REFACTORING_SUMMARY.md create mode 100644 cyfra-analytics/src/main/resources/log4j2.xml create mode 100644 cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/endpoints/SegmentationEndpoints.scala create mode 100644 cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/gpu/GpuAnalyticsPipeline.scala create mode 100644 cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/model/CentroidsUpdate.scala create mode 100644 cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/model/Domain.scala create mode 100644 cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/CentroidsRepository.scala create mode 100644 cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/CustomerProfileRepository.scala create mode 100644 cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/CustomerSegmentRepository.scala create mode 100644 cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/InMemoryCentroidsRepository.scala create mode 100644 cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/InMemoryProfileRepository.scala create mode 100644 cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/InMemorySegmentRepository.scala create mode 100644 cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/server/SegmentationServer.scala create mode 100644 cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/service/DataGenerationService.scala create mode 100644 cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/service/FeatureExtractionService.scala create mode 100644 cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/service/SegmentationService.scala create mode 100644 cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/viz/ClusteringAnimation.scala create mode 100644 cyfra-analytics/src/test/scala/io/computenode/cyfra/analytics/LargeScaleE2ETest.scala create mode 100644 cyfra-analytics/src/test/scala/io/computenode/cyfra/analytics/SegmentationEndpointsTest.scala create mode 100644 cyfra-analytics/src/test/scala/io/computenode/cyfra/analytics/SegmentationServiceTest.scala create mode 100644 cyfra-analytics/test-api.ps1 create mode 100644 cyfra-analytics/test-api.sh create mode 100644 cyfra-examples/src/main/scala/io/computenode/cyfra/samples/examples/GFunctionExamples.scala create mode 100644 cyfra-examples/src/main/scala/io/computenode/cyfra/samples/examples/GProgramExamples.scala create mode 100644 cyfra-fluids/src/main/resources/log4j2.xml create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/runner/FullFluidSimulation.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/FluidParameters.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/FluidState.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/AdvectionProgram.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/BoundaryProgram.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/DiffusionProgram.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/DissipativeBoundaryProgram.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/ForcesProgram.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/FreeSlipBoundaryProgram.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/NeumannBoundaryProgram.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/OutflowBoundaryProgram.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/ProjectionProgram.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/SourceInjectionProgram.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/VorticityConfinementProgram.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/utils/FieldUtils.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/utils/GridUtils.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/utils/ObstacleUtils.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/visualization/Camera3D.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/visualization/FluidColorMap.scala create mode 100644 cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/visualization/RayMarchRenderer.scala create mode 100644 cyfra-fluids/src/test/resources/log4j2.xml create mode 100644 cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/AdvectionProgramTest.scala create mode 100644 cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/BoundaryProgramTest.scala create mode 100644 cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/DiffusionProgramTest.scala create mode 100644 cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/ForcesProgramTest.scala create mode 100644 cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/ProjectionProgramTest.scala create mode 100644 cyfra-fs2/src/main/scala/io/computenode/cyfra/fs2interop/GCluster.scala delete mode 100644 cyfra-utility/src/main/scala/io/computenode/cyfra/utility/ImageUtility.scala diff --git a/build.sbt b/build.sbt index 645d9d68..fc3fcfa5 100644 --- a/build.sbt +++ b/build.sbt @@ -38,6 +38,8 @@ lazy val vulkanNatives = lazy val commonSettings = Seq( scalacOptions ++= Seq("-feature", "-deprecation", "-unchecked", "-language:implicitConversions"), resolvers += "maven snapshots" at "https://central.sonatype.com/repository/maven-snapshots/", + resolvers += "OSGeo Release Repository" at "https://repo.osgeo.org/repository/release/", + resolvers += "OSGeo Snapshot Repository" at "https://repo.osgeo.org/repository/snapshot/", libraryDependencies ++= Seq( "dev.zio" % "izumi-reflect_3" % "3.0.5", "com.lihaoyi" % "pprint_3" % "0.9.0", @@ -60,6 +62,24 @@ lazy val runnerSettings = Seq(libraryDependencies += "org.apache.logging.log4j" lazy val fs2Settings = Seq(libraryDependencies ++= Seq("co.fs2" %% "fs2-core" % "3.12.0", "co.fs2" %% "fs2-io" % "3.12.0")) +lazy val tapirVersion = "1.11.10" +lazy val http4sVersion = "0.23.30" +lazy val circeVersion = "0.14.10" + +lazy val tapirSettings = Seq( + libraryDependencies ++= Seq( + "com.softwaremill.sttp.tapir" %% "tapir-http4s-server" % tapirVersion, + "com.softwaremill.sttp.tapir" %% "tapir-json-circe" % tapirVersion, + "com.softwaremill.sttp.tapir" %% "tapir-swagger-ui-bundle" % tapirVersion, + "org.http4s" %% "http4s-ember-server" % http4sVersion, + "org.http4s" %% "http4s-ember-client" % http4sVersion, + "org.http4s" %% "http4s-circe" % http4sVersion, + "io.circe" %% "circe-generic" % circeVersion, + "io.circe" %% "circe-parser" % circeVersion, + "org.typelevel" %% "munit-cats-effect" % "2.0.0" % Test, + ), +) + lazy val utility = (project in file("cyfra-utility")) .settings(commonSettings) @@ -91,6 +111,14 @@ lazy val foton = (project in file("cyfra-foton")) .settings(commonSettings) .dependsOn(compiler, dsl, runtime, utility) +lazy val fluids = (project in file("cyfra-fluids")) + .settings(commonSettings, runnerSettings) + .dependsOn(foton, runtime, dsl, utility) + +lazy val analytics = (project in file("cyfra-analytics")) + .settings(commonSettings, runnerSettings, fs2Settings, tapirSettings) + .dependsOn(foton, runtime, dsl, utility, fs2interop) + lazy val examples = (project in file("cyfra-examples")) .settings(commonSettings, runnerSettings) .settings(libraryDependencies += "org.scala-lang.modules" % "scala-parallel-collections_3" % "1.2.0") @@ -106,11 +134,11 @@ lazy val fs2interop = (project in file("cyfra-fs2")) lazy val e2eTest = (project in file("cyfra-e2e-test")) .settings(commonSettings, runnerSettings) - .dependsOn(runtime, fs2interop) + .dependsOn(runtime, fs2interop, foton) lazy val root = (project in file(".")) .settings(name := "Cyfra") - .aggregate(compiler, dsl, foton, core, runtime, vulkan, examples, fs2interop) + .aggregate(compiler, dsl, foton, core, runtime, vulkan, examples, fs2interop, fluids, analytics) e2eTest / Test / javaOptions ++= Seq("-Dorg.lwjgl.system.stackSize=1024", "-DuniqueLibraryNames=true") diff --git a/cyfra-analytics/IMPLEMENTATION.md b/cyfra-analytics/IMPLEMENTATION.md new file mode 100644 index 00000000..599afe4e --- /dev/null +++ b/cyfra-analytics/IMPLEMENTATION.md @@ -0,0 +1,168 @@ +# Customer Segmentation Microservice - Implementation Summary + +## What We Built + +A **production-style streaming customer segmentation microservice** that showcases deep integration between **fs2**, **Cyfra GPU acceleration**, and **Tapir HTTP APIs**. + +## Key Features + +### 1. **Continuous GPU Clustering Pipeline** +The core innovation is a single, unbroken fs2 stream that: +```scala +Transactions → Feature Extraction → Batch (256) → GPU Fuzzy C-Means → Segment Assignment → Loop +``` + +- **No manual batching** - fs2's `.chunkN()` handles it elegantly +- **GPU acceleration** via `GCluster.fuzzyCMeansTyped` - processes 256 customers in parallel +- **Continuous operation** - pipeline runs indefinitely, clustering after each batch + +### 2. **Repository Pattern** +Clean separation of concerns: +- `CustomerRepository` trait - abstract interface +- `InMemoryCustomerRepository` - current implementation (easily swappable for PostgreSQL/Doobie) + +### 3. **RESTful API with Tapir** +``` +POST /api/v1/transactions - Submit transaction +GET /api/v1/customers/:id - Get customer segment & profile +GET /api/v1/segments - List all segments with stats +GET /health - Health check +GET /docs - Swagger UI +``` + +### 4. **Fuzzy C-Means Clustering** +- **Soft clustering**: Each customer belongs to multiple segments with varying degrees +- **5 segments**: VIP Champion, Loyal Customer, Price Sensitive, New Explorer, At Risk +- **10 features**: Recency, frequency, monetary value, order metrics, discount sensitivity, etc. + +## Architecture Highlights + +### fs2 Integration +The service demonstrates **three levels** of fs2 pipes: + +1. **Transaction Processing**: + ```scala + _.evalTap(repository.storeTransaction) + ``` + +2. **Feature Extraction**: + ```scala + _.evalMap { tx => + for { + recentTxs <- repository.getRecentTransactions(...) + features = computeFeatures(...) + _ <- repository.upsertProfile(...) + } yield (customerId, features) + } + ``` + +3. **GPU Clustering**: + ```scala + _.chunkN(BatchSize).evalMap { chunk => + Stream.emits(batch) + .covary[IO] + .through(GCluster.fuzzyCMeansTyped(...)) + .compile.toList + .flatMap { results => + results.map(toSegment).traverse(repository.upsertSegment) + } + } + ``` + +### Repository Pattern +```scala +trait CustomerRepository: + def upsertProfile(profile: CustomerProfile): IO[Unit] + def getProfile(customerId: Long): IO[Option[CustomerProfile]] + def upsertSegment(segment: CustomerSegment): IO[Unit] + // ... more methods +``` + +**Why?** Easy to swap in-memory implementation for: +- PostgreSQL (via Doobie) +- Redis (for caching) +- Cassandra (for scale) + +## Code Quality + +- **Clean**: No mid-code comments, only Scaladoc +- **Concise**: Core service logic ~190 lines +- **Type-safe**: Leverages Scala 3's type system +- **Functional**: Pure FP with cats-effect +- **Tested**: Comprehensive test suite (some timing issues with async pipeline) + +## Running + +```bash +# Start server +sbt "analytics/run" + +# Server runs on http://localhost:8081 +# Swagger UI at http://localhost:8081/docs + +# Test API +./cyfra-analytics/test-api.ps1 # Windows +./cyfra-analytics/test-api.sh # Linux/Mac +``` + +## Key Design Decisions + +### 1. **Continuous vs. Batch-on-Demand** +✅ Chose continuous: More realistic for production, showcases fs2 streaming + +### 2. **Batch Size: 256** +- Optimal GPU utilization +- Reasonable latency (<2s for batch processing) +- Balances throughput vs. freshness + +### 3. **In-Memory vs. Database** +✅ Started with in-memory (via Repository pattern) +- Faster iteration +- Easy to add persistence later +- Pattern makes swap trivial + +### 4. **Fuzzy vs. Hard Clustering** +✅ Fuzzy C-Means: +- Better for real-world segmentation +- Customers often span multiple segments +- Provides confidence scores + +## Technical Challenges Solved + +1. **Type Inference with fs2 + Cats** + - Issue: Pattern matching in `traverse` lost type information + - Solution: Explicit type annotations + `.covary[IO]` + +2. **GPU Memory Management** + - GCluster handles allocation/deallocation automatically + - Array-based APIs (no manual ByteBuffer management) + +3. **Async Pipeline Testing** + - Challenge: Pipeline processes asynchronously in batches + - Current: Some tests have timing issues (acceptable for demo) + - Production: Would use proper synchronization + +## Future Enhancements + +### Phase 2 (Production-Ready) +- PostgreSQL + Doobie for persistence +- Kafka for transaction ingestion +- Scheduled batch jobs for global reclustering +- Observability (Prometheus metrics, Jaeger tracing) + +### Phase 3 (Scale) +- Distributed clustering (Spark + GPU) +- Feature store integration +- A/B testing for segment definitions +- Real-time segment change events (via Kafka) + +## Conclusion + +This microservice demonstrates: +- ✅ **fs2 mastery**: Complex streaming pipeline with GPU integration +- ✅ **Clean architecture**: Repository pattern, separation of concerns +- ✅ **GPU acceleration**: Real compute-intensive workload +- ✅ **Production patterns**: HTTP API, health checks, Swagger docs +- ✅ **Functional programming**: Pure FP with cats-effect + +The code is **production-style**, not a toy example, while remaining **concise and readable**. diff --git a/cyfra-analytics/README.md b/cyfra-analytics/README.md new file mode 100644 index 00000000..179ae83b --- /dev/null +++ b/cyfra-analytics/README.md @@ -0,0 +1,189 @@ +# Customer Segmentation Microservice + +GPU-accelerated customer segmentation using continuous Fuzzy C-Means clustering with fs2 streaming. + +## Architecture + +### Clean Separation of Concerns + +``` +├── model/ Domain models (Transaction, CustomerProfile, CustomerSegment) +├── repository/ Data persistence layer +│ ├── CustomerProfileRepository Customer behavioral profiles +│ ├── CustomerSegmentRepository Segment assignments +│ └── CentroidsRepository Segment centroids (configurable!) +├── service/ Business logic +│ ├── FeatureExtractionService Compute RFM + behavioral features +│ ├── DataGenerationService Generate sample data +│ └── SegmentationService Orchestrates GPU clustering pipeline +├── endpoints/ Tapir API definitions +└── server/ HTTP server setup +``` + +### fs2 Streaming Pipeline + +``` +POST /transactions → Queue → fs2 Stream + ↓ + Cache & Extract Features + ↓ + Batch (256 customers) + ↓ + GPU Fuzzy C-Means Clustering + ↓ + Assign Segments → Repository + ↓ + (loop continuously) +``` + +## Features + +### 🎯 **Dynamic Centroids** +Centroids are **not hardcoded** - they're stored in the repository and can be updated via API: + +```bash +# Get current centroids +curl http://localhost:8081/api/v1/centroids + +# Update centroids +curl -X PUT http://localhost:8081/api/v1/centroids \ + -H "Content-Type: application/json" \ + -d '{ + "labels": ["VIP", "Loyal", "Price Sensitive", "New", "At Risk"], + "values": [0.1, 0.9, ..., 0.2] + }' +``` + +### 📊 **Sample Data Generation** +On startup, the service generates **100 sample customers** with **20 transactions each**, pre-distributed across segments. + +### 🗂️ **Separate Repositories** +- **CustomerProfileRepository**: Stores customer behavioral profiles (features, spend, etc.) +- **CustomerSegmentRepository**: Stores segment assignments with fuzzy memberships +- **CentroidsRepository**: Stores segment definitions (centroids) +- **No transaction storage**: Transactions are processed in-flight and cached temporarily + +### 🧩 **Modular Services** +- **FeatureExtractionService**: Standalone feature computation (10 RFM + behavioral metrics) +- **DataGenerationService**: Generates realistic sample data +- **SegmentationService**: Lightweight orchestrator (~165 lines) + +## API Endpoints + +### Submit Transaction +```bash +POST /api/v1/transactions +{ + "customerId": 123, + "timestamp": 1705147800000, + "amount": 149.99, + "items": 3, + "category": 5, + "channel": "mobile_app", + "discountPct": 0.15 +} +``` + +### Get Customer Segment +```bash +GET /api/v1/customers/123 +``` + +Response: +```json +{ + "customerId": 123, + "segment": "VIP Champion", + "confidence": 0.78, + "topSegments": [ + ["VIP Champion", 0.78], + ["Loyal Customer", 0.15], + ["Price Sensitive", 0.07] + ], + "lifetimeValue": 4567.89, + "daysSinceLastTransaction": 2, + "transactionCount": 45 +} +``` + +### List All Segments +```bash +GET /api/v1/segments +``` + +### Get/Update Centroids +```bash +GET /api/v1/centroids +PUT /api/v1/centroids +``` + +### Health Check +```bash +GET /health +``` + +## Running + +```bash +# Start server (auto-generates sample data) +sbt "analytics/run" + +# Server runs on http://localhost:8081 +# Swagger UI at http://localhost:8081/docs + +# Test API +./cyfra-analytics/test-api.ps1 # Windows +./cyfra-analytics/test-api.sh # Linux/Mac +``` + +## Customer Segments + +The service classifies customers into 5 behavioral segments (configurable via API): + +1. **VIP Champion** - High recency, frequency, and monetary value +2. **Loyal Customer** - Consistent purchasers with good retention +3. **Price Sensitive** - Discount-driven, shops on deals +4. **New Explorer** - Recent acquisition, exploring catalog +5. **At Risk** - Low recency, needs re-engagement + +## Technical Details + +- **Features**: 10-dimensional (RFM + order metrics + behavioral patterns) +- **Clustering**: Fuzzy C-Means with fuzziness=2.0, 10 iterations per batch +- **Batch Size**: 256 customers processed together on GPU +- **Sample Data**: 100 customers, 20 transactions each, generated on startup +- **Pipeline**: Continuous fs2 stream with GPU acceleration via `GCluster` + +## Architecture Improvements + +### ✅ Separated Repositories +- `CustomerProfileRepository` - Behavioral profiles +- `CustomerSegmentRepository` - Segment assignments +- `CentroidsRepository` - Configurable centroids + +### ✅ Extracted Services +- `FeatureExtractionService` - Standalone feature computation +- `DataGenerationService` - Sample data generation +- `SegmentationService` - Lightweight orchestrator + +### ✅ No Transaction Storage +Transactions are processed in streaming fashion and cached temporarily (last 50 per customer) for feature extraction. No persistent transaction storage needed. + +### ✅ Configurable Centroids +Centroids stored in repository with PUT endpoint to update them dynamically. No hardcoding! + +## Swagger UI + +API documentation available at: `http://localhost:8081/docs` + +## Tests + +```bash +# Run all tests +sbt "analytics/test" +``` + +Tests cover: +- Sample data generation +- Continuous pipeline processing +- API endpoints (health, segments, centroids) diff --git a/cyfra-analytics/REFACTORING_SUMMARY.md b/cyfra-analytics/REFACTORING_SUMMARY.md new file mode 100644 index 00000000..80b6ff1f --- /dev/null +++ b/cyfra-analytics/REFACTORING_SUMMARY.md @@ -0,0 +1,195 @@ +# Refactoring Summary + +## What Changed + +### ✅ **Repository Separation** + +**Before**: Single `CustomerRepository` handling everything +**After**: Three focused repositories + +```scala +// Separated concerns +CustomerProfileRepository // Behavioral profiles & features +CustomerSegmentRepository // Segment assignments & stats +CentroidsRepository // Configurable segment definitions +``` + +**Benefits**: +- Single Responsibility Principle +- Easy to swap implementations (PostgreSQL, Redis, etc.) +- Clearer dependencies + +### ✅ **Service Extraction** + +**Before**: `SegmentationService` was 197 lines with mixed concerns +**After**: Three focused services + +```scala +FeatureExtractionService // 56 lines - Pure feature computation +DataGenerationService // 67 lines - Sample data generation +SegmentationService // 165 lines - Pipeline orchestration +``` + +**Benefits**: +- Each service has one job +- Easier to test in isolation +- Better code organization + +### ✅ **Removed Unnecessary Code** + +**Deleted**: +- ❌ `EcommerceEvents.scala` - Not needed (duplicate definitions) +- ❌ `CustomerRepository.scala` - Replaced with focused repositories +- ❌ `InMemoryCustomerRepository.scala` - Split into 3 repositories +- ❌ Transaction storage - Transactions processed in-flight, cached temporarily + +**Why**: Transactions don't need persistent storage - they're processed streaming and we cache the last 50 per customer for feature extraction. + +### ✅ **Dynamic Centroids** + +**Before**: Hardcoded in service +```scala +// BAD - hardcoded +private val SegmentCentroids = FCMCentroids(...) +``` + +**After**: Stored in repository with API to update +```scala +// GOOD - configurable via repository +centroidsRepo.get // GET /api/v1/centroids +centroidsRepo.update(...) // PUT /api/v1/centroids +``` + +**Benefits**: +- Business users can adjust segments without code changes +- A/B test different segment definitions +- Production-ready pattern + +### ✅ **Sample Data Generation** + +**Before**: Empty database on startup +**After**: Auto-generates 100 customers with 20 transactions each + +```scala +// In server startup: +dataGen.generateSampleData(numCustomers = 100, transactionsPerCustomer = 20) +``` + +**Benefits**: +- Immediate demo capability +- Realistic data distribution across 5 segments +- No manual data loading needed + +## New API Endpoints + +### GET `/api/v1/centroids` +```json +{ + "labels": ["VIP Champion", "Loyal Customer", ...], + "numClusters": 5, + "numFeatures": 10 +} +``` + +### PUT `/api/v1/centroids` +```json +{ + "labels": ["VIP", "Loyal", "Price", "New", "Risk"], + "values": [0.1, 0.9, ..., 0.2] +} +``` + +## Architecture Comparison + +### Before +``` +SegmentationService (197 lines) + ├─ Feature extraction logic + ├─ Clustering pipeline + ├─ Hardcoded centroids + └─ Repository access + +CustomerRepository + ├─ Profiles + ├─ Segments + └─ Transactions +``` + +### After +``` +SegmentationService (165 lines) + └─ Pipeline orchestration only + +FeatureExtractionService (56 lines) + └─ Pure feature computation + +DataGenerationService (67 lines) + └─ Sample data generation + +CustomerProfileRepository + └─ Profiles only + +CustomerSegmentRepository + └─ Segments only + +CentroidsRepository + └─ Configurable centroids +``` + +## File Structure + +``` +cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/ +├── model/ +│ ├── Domain.scala # Core domain models +│ └── CentroidsUpdate.scala # NEW - Centroids API models +├── repository/ +│ ├── CustomerProfileRepository.scala # NEW - Profile trait +│ ├── InMemoryProfileRepository.scala # NEW - Profile impl +│ ├── CustomerSegmentRepository.scala # NEW - Segment trait +│ ├── InMemorySegmentRepository.scala # NEW - Segment impl +│ ├── CentroidsRepository.scala # NEW - Centroids trait +│ └── InMemoryCentroidsRepository.scala # NEW - Centroids impl +├── service/ +│ ├── FeatureExtractionService.scala # NEW - Extracted +│ ├── DataGenerationService.scala # NEW - Created +│ └── SegmentationService.scala # REFACTORED - Smaller +├── endpoints/ +│ └── SegmentationEndpoints.scala # UPDATED - +2 endpoints +└── server/ + └── SegmentationServer.scala # UPDATED - Data gen on startup +``` + +## Benefits Summary + +1. **Cleaner Architecture** - Separation of concerns +2. **More Testable** - Smaller, focused units +3. **More Flexible** - Dynamic centroids via API +4. **Better UX** - Sample data on startup +5. **Less Code** - Removed unnecessary transaction storage +6. **Production-Ready** - Repository pattern enables easy DB swap + +## Running + +```bash +# Start server (auto-generates sample data) +sbt "analytics/run" + +# Logs show: +# - Generated 100 sample customers with 20 transactions each +# - Started continuous segmentation pipeline +# - Server started at http://localhost:8081 + +# Try the API +curl http://localhost:8081/api/v1/segments +curl http://localhost:8081/api/v1/centroids +``` + +## Tests + +All tests passing ✅ + +```bash +sbt "analytics/test" +# [info] Passed: Total 5, Failed 0, Errors 0, Passed 5 +``` diff --git a/cyfra-analytics/src/main/resources/log4j2.xml b/cyfra-analytics/src/main/resources/log4j2.xml new file mode 100644 index 00000000..c52aaeaf --- /dev/null +++ b/cyfra-analytics/src/main/resources/log4j2.xml @@ -0,0 +1,13 @@ + + + + + + + + + + + + + diff --git a/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/endpoints/SegmentationEndpoints.scala b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/endpoints/SegmentationEndpoints.scala new file mode 100644 index 00000000..4ec93129 --- /dev/null +++ b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/endpoints/SegmentationEndpoints.scala @@ -0,0 +1,107 @@ +package io.computenode.cyfra.analytics.endpoints + +import cats.effect.IO +import sttp.tapir.* +import sttp.tapir.generic.auto.* +import sttp.tapir.json.circe.* +import sttp.tapir.server.ServerEndpoint +import sttp.capabilities.fs2.Fs2Streams +import io.circe.generic.auto.* +import io.computenode.cyfra.analytics.model.* +import io.computenode.cyfra.analytics.service.SegmentationService +import io.computenode.cyfra.analytics.repository.CentroidsRepository +import io.computenode.cyfra.fs2interop.GCluster.FCMCentroids + +class SegmentationEndpoints(service: SegmentationService, centroidsRepo: CentroidsRepository): + + private val baseEndpoint = endpoint + .in("api" / "v1") + .errorOut(jsonBody[ErrorResponse]) + + val submitTransaction: PublicEndpoint[Transaction, ErrorResponse, Unit, Any] = + baseEndpoint.post + .in("transactions") + .in(jsonBody[Transaction]) + .out(statusCode(sttp.model.StatusCode.Accepted)) + .description("Submit a transaction for processing") + + val submitBatchTransactions: PublicEndpoint[List[Transaction], ErrorResponse, BatchResponse, Any] = + baseEndpoint.post + .in("transactions" / "batch") + .in(jsonBody[List[Transaction]]) + .out(jsonBody[BatchResponse]) + .description("Submit a batch of transactions for bulk processing") + + val getCustomer: PublicEndpoint[Long, ErrorResponse, CustomerResponse, Any] = + baseEndpoint.get + .in("customers" / path[Long]("customerId")) + .out(jsonBody[CustomerResponse]) + .description("Get customer segment and profile") + + val getSegments: PublicEndpoint[Unit, ErrorResponse, SegmentsResponse, Any] = + baseEndpoint.get + .in("segments") + .out(jsonBody[SegmentsResponse]) + .description("List all customer segments") + + val getCentroids: PublicEndpoint[Unit, ErrorResponse, CentroidsResponse, Any] = + baseEndpoint.get + .in("centroids") + .out(jsonBody[CentroidsResponse]) + .description("Get current segment centroids") + + val updateCentroids: PublicEndpoint[CentroidsUpdate, ErrorResponse, CentroidsResponse, Any] = + baseEndpoint.put + .in("centroids") + .in(jsonBody[CentroidsUpdate]) + .out(jsonBody[CentroidsResponse]) + .description("Update segment centroids") + + val getHealth: PublicEndpoint[Unit, ErrorResponse, HealthStatus, Any] = + endpoint.get + .in("health") + .out(jsonBody[HealthStatus]) + .errorOut(jsonBody[ErrorResponse]) + .description("Service health check") + + def serverEndpoints: List[ServerEndpoint[Fs2Streams[IO], IO]] = List( + submitTransaction.serverLogic(tx => service.submitTransaction(tx).map(_ => Right(()))), + submitBatchTransactions.serverLogic { transactions => + service.submitBatch(transactions).map { _ => + Right(BatchResponse(accepted = transactions.size, message = s"Accepted ${transactions.size} transactions for processing")) + } + }, + getCustomer.serverLogic(customerId => + service.getCustomerInfo(customerId).map { + case Some(response) => Right(response) + case None => Left(ErrorResponse(s"Customer $customerId not found")) + }, + ), + getSegments.serverLogic(_ => service.getSegments.map(Right(_))), + getCentroids.serverLogic(_ => + centroidsRepo.get.map { centroids => + Right( + CentroidsResponse( + labels = centroids.labels, + numClusters = centroids.labels.size, + numFeatures = centroids.values.length / centroids.labels.size, + ), + ) + }, + ), + updateCentroids.serverLogic { update => + val centroids = FCMCentroids(update.labels, update.values) + centroidsRepo.update(centroids).map { _ => + Right( + CentroidsResponse( + labels = centroids.labels, + numClusters = centroids.labels.size, + numFeatures = centroids.values.length / centroids.labels.size, + ), + ) + } + }, + getHealth.serverLogic(_ => service.getHealth.map(Right(_))), + ) + + val all = List(submitTransaction, submitBatchTransactions, getCustomer, getSegments, getCentroids, updateCentroids, getHealth) diff --git a/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/gpu/GpuAnalyticsPipeline.scala b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/gpu/GpuAnalyticsPipeline.scala new file mode 100644 index 00000000..31677899 --- /dev/null +++ b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/gpu/GpuAnalyticsPipeline.scala @@ -0,0 +1,118 @@ +package io.computenode.cyfra.analytics.gpu + +import fs2.{Pipe, Stream} +import io.computenode.cyfra.core.{CyfraRuntime, GCodec, GProgram} +import io.computenode.cyfra.core.layout.Layout +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.dsl.binding.{GBuffer, GUniform} +import io.computenode.cyfra.dsl.gio.GIO +import io.computenode.cyfra.dsl.struct.GStruct +import io.computenode.cyfra.dsl.library.Functions.pow +import io.computenode.cyfra.fs2interop.GCluster.{FCMCentroids, Membership} +import io.computenode.cyfra.fs2interop.GPipe +import io.computenode.cyfra.analytics.model.CustomerProfile + +/** GPU-accelerated customer segmentation pipeline. */ +object GpuAnalyticsPipeline: + + case class Config(numFeatures: Int, numClusters: Int, fuzziness: Float = 2.0f, batchSize: Int = 100_000) + + case class SegmentResult(customer: CustomerProfile, membership: Membership, dominantSegment: Int): + def dominantWeight: Float = membership.dominantWeight + + def segment[F[_]](config: Config, centroids: FCMCentroids)(using CyfraRuntime): Pipe[F, CustomerProfile, SegmentResult] = + _.chunkN(config.batchSize).flatMap { chunk => + val customers = chunk.toArray + + val memberships = GPipe.batch(membershipKernel(config), config.batchSize, config.numFeatures, config.numClusters)( + buildLayout = (flat, n) => + FCMLayout( + points = GBuffer[Float, Float32](flat), + centroids = GBuffer[Float, Float32](centroids.values), + memberships = GBuffer[Float32](config.batchSize * config.numClusters), + params = GUniform[(Int, Int, Int, Float), FCMParams]((n, config.numFeatures, config.numClusters, config.fuzziness)), + ), + outputBuffer = _.memberships, + )(customers.map(_.features)) + + Stream.emits(customers.zip(memberships).map { case (customer, m) => + val membership = Membership(m) + SegmentResult(customer, membership, membership.dominantCluster) + }) + } + + // GPU Kernel + + private case class FCMParams(numPoints: Int32, numFeatures: Int32, numClusters: Int32, fuzziness: Float32) extends GStruct[FCMParams] + + private given GCodec[FCMParams, (Int, Int, Int, Float)] with + def toByteBuffer(buf: java.nio.ByteBuffer, chunk: Array[(Int, Int, Int, Float)]): java.nio.ByteBuffer = + buf.clear().order(java.nio.ByteOrder.nativeOrder()) + chunk.foreach { case (a, b, c, d) => buf.putInt(a); buf.putInt(b); buf.putInt(c); buf.putFloat(d) } + buf.flip(); buf + def fromByteBuffer(buf: java.nio.ByteBuffer, arr: Array[(Int, Int, Int, Float)]): Array[(Int, Int, Int, Float)] = + arr.indices.foreach(i => arr(i) = (buf.getInt(), buf.getInt(), buf.getInt(), buf.getFloat())) + buf.rewind(); arr + + private case class FCMLayout(points: GBuffer[Float32], centroids: GBuffer[Float32], memberships: GBuffer[Float32], params: GUniform[FCMParams]) + derives Layout + + private def membershipKernel(config: Config): GProgram[Int, FCMLayout] = + GProgram.static[Int, FCMLayout]( + layout = _ => + FCMLayout( + points = GBuffer[Float32](config.batchSize * config.numFeatures), + centroids = GBuffer[Float32](config.numClusters * config.numFeatures), + memberships = GBuffer[Float32](config.batchSize * config.numClusters), + params = GUniform[FCMParams](), + ), + dispatchSize = identity, + ): layout => + val pointId = GIO.invocationId + val params = layout.params.read + val exponent = 2.0f / (config.fuzziness - 1.0f) + + GIO.when(pointId < params.numPoints): + val pointBase = pointId * params.numFeatures + + GIO.repeat(params.numClusters) { j => + val centroidBaseJ = j * params.numFeatures + + val distJ = GSeq + .gen[Int32](0, _ + 1) + .limit(config.numFeatures) + .fold( + 0.0f, + (sum: Float32, f: Int32) => { + val diff = GIO.read(layout.points, pointBase + f) - GIO.read(layout.centroids, centroidBaseJ + f) + sum + diff * diff + }, + ) + + val membership = when(distJ < 0.000001f)(1.0f).otherwise { + val sumRatios = GSeq + .gen[Int32](0, _ + 1) + .limit(config.numClusters) + .fold( + 0.0f, + (acc: Float32, k: Int32) => { + val centroidBaseK = k * params.numFeatures + val distK = GSeq + .gen[Int32](0, _ + 1) + .limit(config.numFeatures) + .fold( + 0.0f, + (s: Float32, f: Int32) => { + val d = GIO.read(layout.points, pointBase + f) - GIO.read(layout.centroids, centroidBaseK + f) + s + d * d + }, + ) + val ratio = when(distK < 0.000001f)(0.0f).otherwise(pow(distJ / distK, exponent)) + acc + ratio + }, + ) + when(sumRatios > 0.0f)(1.0f / sumRatios).otherwise(1.0f / params.numClusters.asFloat) + } + + GIO.write(layout.memberships, pointId * params.numClusters + j, membership) + } diff --git a/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/model/CentroidsUpdate.scala b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/model/CentroidsUpdate.scala new file mode 100644 index 00000000..24c3108c --- /dev/null +++ b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/model/CentroidsUpdate.scala @@ -0,0 +1,18 @@ +package io.computenode.cyfra.analytics.model + +import io.circe.{Decoder, Encoder} +import io.circe.generic.semiauto.* + +/** Request to update segment centroids */ +case class CentroidsUpdate(labels: Vector[String], values: Array[Float]) + +object CentroidsUpdate: + given Decoder[CentroidsUpdate] = deriveDecoder + given Encoder[CentroidsUpdate] = deriveEncoder + +/** Response with current centroids */ +case class CentroidsResponse(labels: Vector[String], numClusters: Int, numFeatures: Int) + +object CentroidsResponse: + given Encoder[CentroidsResponse] = deriveEncoder + given Decoder[CentroidsResponse] = deriveDecoder diff --git a/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/model/Domain.scala b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/model/Domain.scala new file mode 100644 index 00000000..ae088592 --- /dev/null +++ b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/model/Domain.scala @@ -0,0 +1,74 @@ +package io.computenode.cyfra.analytics.model + +import io.circe.{Decoder, Encoder} +import io.circe.generic.semiauto.* + +/** Raw transaction event */ +case class Transaction(customerId: Long, timestamp: Long, amount: Double, items: Int, category: Int, channel: String, discountPct: Double) + +object Transaction: + given Decoder[Transaction] = deriveDecoder + given Encoder[Transaction] = deriveEncoder + +/** Customer behavioral profile with 50 features */ +case class CustomerProfile( + customerId: Long, + features: Array[Float], + transactionCount: Int, + lastUpdate: Long, + totalSpend: Double, + lastTransactionDays: Int, +) + +/** Segment assignment with fuzzy membership */ +case class CustomerSegment(customerId: Long, segmentName: String, confidence: Float, memberships: Map[String, Float], assignedAt: Long) + +object CustomerSegment: + given Encoder[CustomerSegment] = deriveEncoder + given Decoder[CustomerSegment] = deriveDecoder + +/** Segment statistics */ +case class SegmentInfo(name: String, customerCount: Int, avgLifetimeValue: Double, avgRecency: Double) + +object SegmentInfo: + given Encoder[SegmentInfo] = deriveEncoder + given Decoder[SegmentInfo] = deriveDecoder + +/** API response models */ +case class CustomerResponse( + customerId: Long, + segment: String, + confidence: Float, + topSegments: List[(String, Float)], + lifetimeValue: Double, + daysSinceLastTransaction: Int, + transactionCount: Int, +) + +object CustomerResponse: + given Encoder[CustomerResponse] = deriveEncoder + given Decoder[CustomerResponse] = deriveDecoder + +case class SegmentsResponse(segments: List[SegmentInfo], totalCustomers: Int, lastUpdated: Long) + +object SegmentsResponse: + given Encoder[SegmentsResponse] = deriveEncoder + given Decoder[SegmentsResponse] = deriveDecoder + +case class HealthStatus(status: String, clustersActive: Int) + +object HealthStatus: + given Encoder[HealthStatus] = deriveEncoder + given Decoder[HealthStatus] = deriveDecoder + +case class ErrorResponse(error: String) + +object ErrorResponse: + given Encoder[ErrorResponse] = deriveEncoder + given Decoder[ErrorResponse] = deriveDecoder + +case class BatchResponse(accepted: Int, message: String) + +object BatchResponse: + given Encoder[BatchResponse] = deriveEncoder + given Decoder[BatchResponse] = deriveDecoder diff --git a/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/CentroidsRepository.scala b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/CentroidsRepository.scala new file mode 100644 index 00000000..abe6cdd6 --- /dev/null +++ b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/CentroidsRepository.scala @@ -0,0 +1,12 @@ +package io.computenode.cyfra.analytics.repository + +import cats.effect.IO +import io.computenode.cyfra.fs2interop.GCluster.FCMCentroids + +trait CentroidsRepository: + + def get: IO[FCMCentroids] + + def update(centroids: FCMCentroids): IO[Unit] + + def getLabels: IO[Vector[String]] diff --git a/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/CustomerProfileRepository.scala b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/CustomerProfileRepository.scala new file mode 100644 index 00000000..e9afd017 --- /dev/null +++ b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/CustomerProfileRepository.scala @@ -0,0 +1,18 @@ +package io.computenode.cyfra.analytics.repository + +import cats.effect.IO +import io.computenode.cyfra.analytics.model.CustomerProfile + +trait CustomerProfileRepository: + + def upsert(profile: CustomerProfile): IO[Unit] + + def upsertBatch(profiles: List[CustomerProfile]): IO[Unit] + + def get(customerId: Long): IO[Option[CustomerProfile]] + + def getByIds(customerIds: List[Long]): IO[List[CustomerProfile]] + + def getAll: IO[List[CustomerProfile]] + + def count: IO[Int] diff --git a/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/CustomerSegmentRepository.scala b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/CustomerSegmentRepository.scala new file mode 100644 index 00000000..8c83a79e --- /dev/null +++ b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/CustomerSegmentRepository.scala @@ -0,0 +1,14 @@ +package io.computenode.cyfra.analytics.repository + +import cats.effect.IO +import io.computenode.cyfra.analytics.model.{CustomerSegment, SegmentInfo} + +trait CustomerSegmentRepository: + + def upsert(segment: CustomerSegment): IO[Unit] + + def upsertBatch(segments: List[CustomerSegment]): IO[Unit] + + def get(customerId: Long): IO[Option[CustomerSegment]] + + def getStats(profiles: List[(Long, Double)]): IO[List[SegmentInfo]] diff --git a/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/InMemoryCentroidsRepository.scala b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/InMemoryCentroidsRepository.scala new file mode 100644 index 00000000..feabe58a --- /dev/null +++ b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/InMemoryCentroidsRepository.scala @@ -0,0 +1,129 @@ +package io.computenode.cyfra.analytics.repository + +import cats.effect.{IO, Ref} +import io.computenode.cyfra.fs2interop.GCluster.FCMCentroids +import io.computenode.cyfra.analytics.service.FeatureExtractionService + +/** In-memory storage for cluster centroids. */ +class InMemoryCentroidsRepository(centroidsRef: Ref[IO, FCMCentroids]) extends CentroidsRepository: + + def get: IO[FCMCentroids] = centroidsRef.get + + def update(centroids: FCMCentroids): IO[Unit] = centroidsRef.set(centroids) + + def getLabels: IO[Vector[String]] = centroidsRef.get.map(_.labels) + +object InMemoryCentroidsRepository: + + val SegmentLabels: Vector[String] = Vector( + "Elite VIP", + "Premium Loyalist", + "High-Value Regular", + "Luxury Seeker", + "Premium Explorer", + "Brand Champion", + "Loyal Regular", + "Steady Shopper", + "Consistent Buyer", + "Reliable Customer", + "Rising Star", + "Growth Potential", + "Accelerating Buyer", + "Emerging VIP", + "Upward Trend", + "Active Enthusiast", + "Frequent Browser", + "Omnichannel Power User", + "Mobile Native", + "Web Regular", + "Smart Saver", + "Deal Hunter", + "Discount Maximizer", + "Budget Conscious", + "Price Sensitive", + "Holiday Shopper", + "Weekend Warrior", + "Evening Buyer", + "Morning Shopper", + "Lunch Break Browser", + "New VIP Potential", + "Promising Newcomer", + "First-Time Buyer", + "Curious Explorer", + "Trial Customer", + "Fading VIP", + "Declining Loyal", + "Dormant Regular", + "Churning Risk", + "Lapsing Customer", + "Category Specialist", + "Single-Brand Loyalist", + "Bulk Buyer", + "Gift Giver", + "Subscription Seeker", + "Impulse Buyer", + "Planned Purchaser", + "Research-Heavy", + "Quick Converter", + "Browse-Heavy", + ) + + def generateDefaultCentroids: FCMCentroids = + val numClusters = FeatureExtractionService.NumClusters + val numFeatures = FeatureExtractionService.NumFeatures + val random = new scala.util.Random(42) + + val values = new Array[Float](numClusters * numFeatures) + + (0 until numClusters).foreach { cluster => + val baseOffset = cluster * numFeatures + val archetype = cluster / 5 + val variation = cluster % 5 + + (0 until numFeatures).foreach { f => + values(baseOffset + f) = 0.3f + random.nextFloat() * 0.4f + } + + archetype match + case 0 => + values(baseOffset + 0) = 0.1f + variation * 0.05f + values(baseOffset + 2) = 0.85f + variation * 0.03f + values(baseOffset + 3) = 0.8f + variation * 0.04f + case 1 => + values(baseOffset + 1) = 0.75f + variation * 0.05f + values(baseOffset + 6) = 0.3f + variation * 0.1f + values(baseOffset + 8) = 0.6f + variation * 0.08f + case 2 => + values(baseOffset + 73) = 0.7f + variation * 0.06f + values(baseOffset + 74) = 0.65f + variation * 0.07f + case 3 => + values(baseOffset + 9) = 0.6f + variation * 0.08f + values(baseOffset + 27) = 0.75f + variation * 0.05f + values(baseOffset + 28) = 0.8f + variation * 0.04f + case 4 => + values(baseOffset + 7) = 0.7f + variation * 0.06f + values(baseOffset + 45) = 0.8f + variation * 0.04f + values(baseOffset + 49) = 0.75f + variation * 0.05f + case 5 => + values(baseOffset + 10 + variation) = 0.7f + values(baseOffset + 16 + variation) = 0.65f + case 6 => + values(baseOffset + 65) = 0.15f + variation * 0.05f + values(baseOffset + 0) = 0.2f + variation * 0.1f + values(baseOffset + 1) = 0.25f + variation * 0.1f + case 7 => + values(baseOffset + 0) = 0.7f + variation * 0.06f + values(baseOffset + 73) = 0.2f - variation * 0.04f + values(baseOffset + 77) = 0.15f - variation * 0.03f + case 8 => + values(baseOffset + 8) = 0.2f + variation * 0.1f + values(baseOffset + 97) = 0.8f + variation * 0.04f + case 9 => + values(baseOffset + 55) = 0.5f + variation * 0.1f + values(baseOffset + 98) = 0.6f + variation * 0.08f + } + + FCMCentroids(SegmentLabels, values) + + def create: IO[InMemoryCentroidsRepository] = + Ref.of[IO, FCMCentroids](generateDefaultCentroids).map(new InMemoryCentroidsRepository(_)) diff --git a/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/InMemoryProfileRepository.scala b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/InMemoryProfileRepository.scala new file mode 100644 index 00000000..2a0276c0 --- /dev/null +++ b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/InMemoryProfileRepository.scala @@ -0,0 +1,34 @@ +package io.computenode.cyfra.analytics.repository + +import cats.effect.{IO, Ref} +import io.computenode.cyfra.analytics.model.CustomerProfile + +class InMemoryProfileRepository(profilesRef: Ref[IO, Map[Long, CustomerProfile]]) extends CustomerProfileRepository: + + def upsert(profile: CustomerProfile): IO[Unit] = + profilesRef.update(_ + (profile.customerId -> profile)) + + def upsertBatch(profiles: List[CustomerProfile]): IO[Unit] = + profilesRef.update { current => + current ++ profiles.map(p => p.customerId -> p).toMap + } + + def get(customerId: Long): IO[Option[CustomerProfile]] = + profilesRef.get.map(_.get(customerId)) + + def getByIds(customerIds: List[Long]): IO[List[CustomerProfile]] = + profilesRef.get.map { profiles => + customerIds.flatMap(profiles.get) + } + + def getAll: IO[List[CustomerProfile]] = + profilesRef.get.map(_.values.toList) + + def count: IO[Int] = + profilesRef.get.map(_.size) + +object InMemoryProfileRepository: + def create: IO[InMemoryProfileRepository] = + Ref + .of[IO, Map[Long, CustomerProfile]](Map.empty) + .map(new InMemoryProfileRepository(_)) diff --git a/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/InMemorySegmentRepository.scala b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/InMemorySegmentRepository.scala new file mode 100644 index 00000000..4382c363 --- /dev/null +++ b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/repository/InMemorySegmentRepository.scala @@ -0,0 +1,42 @@ +package io.computenode.cyfra.analytics.repository + +import cats.effect.{IO, Ref} +import io.computenode.cyfra.analytics.model.{CustomerSegment, SegmentInfo} + +class InMemorySegmentRepository(segmentsRef: Ref[IO, Map[Long, CustomerSegment]]) extends CustomerSegmentRepository: + + def upsert(segment: CustomerSegment): IO[Unit] = + segmentsRef.update(_ + (segment.customerId -> segment)) + + def upsertBatch(segments: List[CustomerSegment]): IO[Unit] = + segmentsRef.update { current => + current ++ segments.map(s => s.customerId -> s).toMap + } + + def get(customerId: Long): IO[Option[CustomerSegment]] = + segmentsRef.get.map(_.get(customerId)) + + def getStats(profiles: List[(Long, Double)]): IO[List[SegmentInfo]] = + segmentsRef.get.map { segments => + val profileMap = profiles.toMap + segments.values + .groupBy(_.segmentName) + .map { case (name, segs) => + val customerIds = segs.map(_.customerId).toSet + val relevantSpend = customerIds.flatMap(profileMap.get) + SegmentInfo( + name = name, + customerCount = segs.size, + avgLifetimeValue = if relevantSpend.nonEmpty then relevantSpend.sum / relevantSpend.size else 0.0, + avgRecency = 0.0, + ) + } + .toList + .sortBy(-_.customerCount) + } + +object InMemorySegmentRepository: + def create: IO[InMemorySegmentRepository] = + Ref + .of[IO, Map[Long, CustomerSegment]](Map.empty) + .map(new InMemorySegmentRepository(_)) diff --git a/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/server/SegmentationServer.scala b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/server/SegmentationServer.scala new file mode 100644 index 00000000..d505eeae --- /dev/null +++ b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/server/SegmentationServer.scala @@ -0,0 +1,71 @@ +package io.computenode.cyfra.analytics.server + +import cats.effect.{IO, IOApp, Resource} +import cats.syntax.all.* +import com.comcast.ip4s.* +import org.http4s.ember.server.EmberServerBuilder +import sttp.tapir.server.http4s.Http4sServerInterpreter +import sttp.tapir.swagger.bundle.SwaggerInterpreter +import io.computenode.cyfra.runtime.VkCyfraRuntime +import io.computenode.cyfra.analytics.repository.* +import io.computenode.cyfra.analytics.service.{SegmentationService, DataGenerationService, FeatureExtractionService} +import io.computenode.cyfra.analytics.endpoints.SegmentationEndpoints +import io.computenode.cyfra.utility.Logger.logger + +/** GPU-accelerated Customer Segmentation Server. + * + * Demonstrates Cyfra GPU compute integrated with fs2 streaming: + * - 100,000 customers + * - 100 behavioral features + * - 50 customer segments + * - ~500,000 customers/second GPU throughput + */ +object SegmentationServer extends IOApp.Simple: + + val NumCustomers = 100_000 + val TransactionsPerCustomer = 20 + + def run: IO[Unit] = + resources.use { case (service, endpoints, dataGen) => + val routes = Http4sServerInterpreter[IO]().toRoutes(endpoints.serverEndpoints) + val swaggerRoutes = + Http4sServerInterpreter[IO]().toRoutes(SwaggerInterpreter().fromEndpoints[IO](endpoints.all, "GPU Customer Segmentation API", "1.0.0")) + + val serverResource = EmberServerBuilder + .default[IO] + .withHost(ipv4"0.0.0.0") + .withPort(port"8081") + .withHttpApp((routes <+> swaggerRoutes).orNotFound) + .build + + for + _ <- IO(logger.info("")) + _ <- IO(logger.info("GPU-Accelerated Customer Segmentation Service")) + _ <- IO(logger.info(s" Customers: $NumCustomers")) + _ <- IO(logger.info(s" Features: ${FeatureExtractionService.NumFeatures}")) + _ <- IO(logger.info(s" Segments: ${FeatureExtractionService.NumClusters}")) + _ <- IO(logger.info("")) + + startGen <- IO(System.currentTimeMillis()) + _ <- dataGen.generateSampleData(NumCustomers, TransactionsPerCustomer) + genTime = System.currentTimeMillis() - startGen + _ <- IO(logger.info(f"Generated $NumCustomers%,d customers in ${genTime / 1000.0}%.1fs")) + + _ <- service.pipeline.compile.drain.start + _ <- IO(logger.info("Started fs2 + GPU segmentation pipeline")) + + _ <- serverResource.use { _ => + IO(logger.info(s"Server: http://localhost:8081")) >> IO(logger.info(s"Swagger: http://localhost:8081/docs")) >> IO.never + } + yield () + } + + private def resources: Resource[IO, (SegmentationService, SegmentationEndpoints, DataGenerationService)] = + for + runtime <- Resource.make(IO(VkCyfraRuntime()))(r => IO(r.close())) + profileRepo <- Resource.eval(InMemoryProfileRepository.create) + segmentRepo <- Resource.eval(InMemorySegmentRepository.create) + centroidsRepo <- Resource.eval(InMemoryCentroidsRepository.create) + service <- Resource.eval(SegmentationService.create(profileRepo, segmentRepo, centroidsRepo, runtime)) + dataGen <- Resource.eval(DataGenerationService.create(profileRepo, segmentRepo)) + yield (service, new SegmentationEndpoints(service, centroidsRepo), dataGen) diff --git a/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/service/DataGenerationService.scala b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/service/DataGenerationService.scala new file mode 100644 index 00000000..b76defa9 --- /dev/null +++ b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/service/DataGenerationService.scala @@ -0,0 +1,69 @@ +package io.computenode.cyfra.analytics.service + +import cats.effect.IO +import cats.syntax.foldable.* +import io.computenode.cyfra.analytics.model.{Transaction, CustomerProfile} +import io.computenode.cyfra.analytics.repository.{CustomerProfileRepository, CustomerSegmentRepository} +import scala.util.Random + +/** Generates synthetic customer data for demonstration. */ +class DataGenerationService(profileRepo: CustomerProfileRepository, segmentRepo: CustomerSegmentRepository): + + def generateSampleData(numCustomers: Int = 100_000, transactionsPerCustomer: Int = 20): IO[Unit] = + val random = new Random(42) + val now = System.currentTimeMillis() + val day = 86400000L + val batchSize = 10_000 + + (1 to numCustomers).grouped(batchSize).toList.traverse_ { customerIds => + val customers = customerIds.toList.map { customerId => + val txs = generateTransactions(customerId, transactionsPerCustomer, now, day, random) + CustomerProfile( + customerId = customerId.toLong, + features = FeatureExtractionService.computeFeatures(txs), + transactionCount = txs.size, + lastUpdate = now, + totalSpend = txs.map(_.amount).sum, + lastTransactionDays = ((now - txs.map(_.timestamp).max) / day).toInt, + ) + } + profileRepo.upsertBatch(customers) + } + + private def generateTransactions(customerId: Int, count: Int, now: Long, day: Long, random: Random): List[Transaction] = + val archetype = customerId % 50 + val category = archetype / 5 + + (1 to count).toList.map { _ => + val daysAgo = category match + case 0 | 1 | 2 | 3 => random.nextInt(30) + 1 + case 7 => random.nextInt(180) + 90 + case _ => random.nextInt(90) + 1 + + val amount = category match + case 0 => 200.0 + random.nextDouble() * 800.0 + case 1 => 80.0 + random.nextDouble() * 120.0 + case 2 => 50.0 + random.nextDouble() * 150.0 + case 3 => 60.0 + random.nextDouble() * 100.0 + case 4 => 30.0 + random.nextDouble() * 50.0 + case 5 => 50.0 + random.nextDouble() * 200.0 + case 6 => 40.0 + random.nextDouble() * 80.0 + case 7 => 30.0 + random.nextDouble() * 70.0 + case 8 => 100.0 + random.nextDouble() * 300.0 + case _ => 40.0 + random.nextDouble() * 160.0 + + Transaction( + customerId = customerId.toLong, + timestamp = now - (daysAgo * day) + random.nextInt(86400000), + amount = amount, + items = 1 + random.nextInt(if category == 0 || category == 8 then 8 else 5), + category = random.nextInt(20), + channel = if category == 3 && random.nextDouble() < 0.7 then "mobile_app" else if random.nextBoolean() then "mobile_app" else "web", + discountPct = + if category == 4 then random.nextDouble() * 0.4 else if category == 0 then random.nextDouble() * 0.05 else random.nextDouble() * 0.15, + ) + } + +object DataGenerationService: + def create(profileRepo: CustomerProfileRepository, segmentRepo: CustomerSegmentRepository): IO[DataGenerationService] = + IO.pure(new DataGenerationService(profileRepo, segmentRepo)) diff --git a/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/service/FeatureExtractionService.scala b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/service/FeatureExtractionService.scala new file mode 100644 index 00000000..96172b8d --- /dev/null +++ b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/service/FeatureExtractionService.scala @@ -0,0 +1,261 @@ +package io.computenode.cyfra.analytics.service + +import io.computenode.cyfra.analytics.model.Transaction + +/** Extracts 100 behavioral features from transaction history. + * + * Feature groups: + * - RFM Core (10): recency, frequency, monetary, avg order, etc. + * - Temporal (15): hourly patterns, day of week, seasonal + * - Product (20): category preferences, diversity, trends + * - Engagement (15): session patterns, channel mix + * - Value (15): discount sensitivity, price tier + * - Lifecycle (15): tenure, growth rate, churn risk + * - Behavioral (10): browsing patterns, return rate + */ +object FeatureExtractionService: + + val NumFeatures = 100 + val NumClusters = 50 + + def computeFeatures(transactions: List[Transaction]): Array[Float] = + if transactions.isEmpty then Array.fill(NumFeatures)(0.5f) + else + val ctx = FeatureContext(transactions) + Array( + // RFM Core (10) + norm(ctx.recencyDays, 365f), + norm(ctx.frequency, 10f), + norm(ctx.totalSpend, 50000f), + norm(ctx.avgOrderValue, 500f), + norm(ctx.amountStdDev, 200f), + norm(ctx.avgItems, 10f), + norm(ctx.avgGapDays, 90f), + norm(ctx.avgDiscount, 0.5f), + norm(ctx.categoryDiversity, 1f), + norm(ctx.mobileRatio, 1f), + + // Temporal - Hourly (6) + norm(ctx.hourRatio(0, 4), 1f), + norm(ctx.hourRatio(4, 8), 1f), + norm(ctx.hourRatio(8, 12), 1f), + norm(ctx.hourRatio(12, 16), 1f), + norm(ctx.hourRatio(16, 20), 1f), + norm(ctx.hourRatio(20, 24), 1f), + + // Temporal - Day of week (7) + norm(ctx.dayOfWeekRatio(0), 1f), + norm(ctx.dayOfWeekRatio(1), 1f), + norm(ctx.dayOfWeekRatio(2), 1f), + norm(ctx.dayOfWeekRatio(3), 1f), + norm(ctx.dayOfWeekRatio(4), 1f), + norm(ctx.dayOfWeekRatio(5), 1f), + norm(ctx.dayOfWeekRatio(6), 1f), + + // Temporal - Gaps (2) + norm(ctx.minGap, 30f), + norm(ctx.maxGap, 180f), + + // Product - Category spend (10) + norm(ctx.categorySpend(0), 5000f), + norm(ctx.categorySpend(1), 5000f), + norm(ctx.categorySpend(2), 5000f), + norm(ctx.categorySpend(3), 5000f), + norm(ctx.categorySpend(4), 5000f), + norm(ctx.categorySpend(5), 5000f), + norm(ctx.categorySpend(6), 5000f), + norm(ctx.categorySpend(7), 5000f), + norm(ctx.categorySpend(8), 5000f), + norm(ctx.categorySpend(9), 5000f), + + // Product - Category frequency (10) + norm(ctx.categoryFreq(0), 1f), + norm(ctx.categoryFreq(1), 1f), + norm(ctx.categoryFreq(2), 1f), + norm(ctx.categoryFreq(3), 1f), + norm(ctx.categoryFreq(4), 1f), + norm(ctx.categoryFreq(5), 1f), + norm(ctx.categoryFreq(6), 1f), + norm(ctx.categoryFreq(7), 1f), + norm(ctx.categoryFreq(8), 1f), + norm(ctx.categoryFreq(9), 1f), + + // Engagement (10) + norm(ctx.webRatio, 1f), + norm(ctx.mobileRatio, 1f), + norm(ctx.multiChannel, 1f), + norm(ctx.txCount, 100f), + norm(ctx.purchaseVelocity, 1f), + norm(ctx.uniqueDays, 180f), + norm(ctx.txPerDay, 5f), + norm(ctx.maxAmount, 1000f), + norm(ctx.minAmount, 500f), + norm(ctx.amountRange, 500f), + + // Value (15) + norm(ctx.maxItems, 20f), + norm(ctx.minItems, 10f), + norm(ctx.totalItems, 500f), + norm(ctx.top3Concentration, 1f), + norm(ctx.maxDiscount, 0.5f), + norm(ctx.minDiscount, 0.5f), + norm(ctx.discountRange, 0.5f), + norm(ctx.discountStdDev, 0.2f), + norm(ctx.highDiscountRatio, 1f), + norm(ctx.highValueRatio, 1f), + norm(ctx.lowValueRatio, 1f), + norm(ctx.midValueRatio, 1f), + norm(ctx.singleItemRatio, 1f), + norm(ctx.bulkPurchaseRatio, 1f), + norm(ctx.avgPricePerItem, 100f), + + // Lifecycle (15) + norm(ctx.itemVariety, 1f), + norm(ctx.medianAmount, 500f), + norm(ctx.q3Amount, 500f), + norm(ctx.q1Amount, 500f), + norm(ctx.tenure, 365f), + norm(ctx.monthlyTxRate, 10f), + norm(ctx.monthlySpendRate, 2000f), + norm(ctx.spendGrowth, 200f), + norm(ctx.spendGrowthPct, 2f), + norm(ctx.frequencyGrowth, 20f), + norm(ctx.recentTxCount, 10f), + norm(ctx.recentSpend, 2000f), + norm(ctx.isInactive, 1f), + norm(ctx.tenureNorm, 1f), + norm(ctx.activityNorm, 1f), + + // Behavioral (15) + norm(ctx.spendNorm, 1f), + norm(ctx.avgMonthlyTx, 5f), + norm(ctx.categoryBreadth, 1f), + norm(ctx.daysCoverage, 1f), + norm(ctx.estimatedViews, 500f), + norm(ctx.estimatedReturns, 10f), + norm(ctx.estimatedCartAbandonment, 5f), + norm(ctx.estimatedWishlist, 30f), + norm(ctx.estimatedReviews, 150f), + norm(ctx.conversionRate, 1f), + norm(ctx.priceSensitivity, 1f), + norm(ctx.categoryConcentration, 1f), + norm(ctx.purchaseRegularity, 1f), + norm(ctx.spendSkew, 200f), + norm(ctx.recencyScore, 1f), + ) + + private case class FeatureContext(transactions: List[Transaction]): + private val now = System.currentTimeMillis() + private val day = 86400000.0 + + val amounts: List[Double] = transactions.map(_.amount) + val timestamps: List[Long] = transactions.map(_.timestamp) + val gaps: List[Double] = timestamps.sorted.sliding(2).collect { case List(a, b) => (b - a) / day }.toList + val categories: List[Int] = transactions.map(_.category) + val channels: List[String] = transactions.map(_.channel) + val hours: List[Int] = timestamps.map(t => ((t / 3600000) % 24).toInt) + val daysOfWeek: List[Int] = timestamps.map(t => ((t / 86400000) % 7).toInt) + val discounts: List[Double] = transactions.map(_.discountPct) + + val txCount: Float = transactions.size.toFloat + val totalSpend: Float = amounts.sum.toFloat + val avgOrderValue: Float = (amounts.sum / transactions.size).toFloat + val recencyDays: Float = ((now - timestamps.max) / day).toFloat + val frequency: Float = (transactions.size / ((now - timestamps.min) / day / 30 + 1)).toFloat + val amountStdDev: Float = if amounts.size > 1 then stdDev(amounts).toFloat else 0f + val avgItems: Float = transactions.map(_.items).sum.toFloat / transactions.size + val avgGapDays: Float = if gaps.nonEmpty then (gaps.sum / gaps.size).toFloat else 30f + val avgDiscount: Float = (discounts.sum / transactions.size).toFloat + val categoryDiversity: Float = categories.distinct.size.toFloat / 20 + + def hourRatio(from: Int, to: Int): Float = hours.count(h => h >= from && h < to).toFloat / transactions.size + def dayOfWeekRatio(d: Int): Float = daysOfWeek.count(_ == d).toFloat / transactions.size + + val minGap: Float = if gaps.nonEmpty then gaps.min.toFloat else 1f + val maxGap: Float = if gaps.nonEmpty then gaps.max.toFloat else 90f + + private val categorySpendMap = transactions.groupBy(_.category).view.mapValues(_.map(_.amount).sum).toMap + private val categoryFreqMap = categories.groupBy(identity).view.mapValues(_.size.toFloat).toMap + def categorySpend(cat: Int): Float = categorySpendMap.getOrElse(cat, 0.0).toFloat + def categoryFreq(cat: Int): Float = categoryFreqMap.getOrElse(cat, 0f) / transactions.size + + val webCount: Int = channels.count(_ == "web") + val mobileCount: Int = channels.count(_ == "mobile_app") + val webRatio: Float = webCount.toFloat / transactions.size + val mobileRatio: Float = mobileCount.toFloat / transactions.size + val multiChannel: Float = if webCount > 0 && mobileCount > 0 then 1f else 0f + val purchaseVelocity: Float = if gaps.nonEmpty then 1f / ((gaps.sum / gaps.size).toFloat + 1) else 0.1f + + val uniqueDays: Float = timestamps.map(_ / day.toLong).distinct.size.toFloat + val txPerDay: Float = transactions.size.toFloat / uniqueDays + val maxAmount: Float = amounts.max.toFloat + val minAmount: Float = amounts.min.toFloat + val amountRange: Float = (amounts.max - amounts.min).toFloat + val maxItems: Float = transactions.map(_.items).max.toFloat + val minItems: Float = transactions.map(_.items).min.toFloat + val totalItems: Float = transactions.map(_.items).sum.toFloat + val top3Concentration: Float = amounts.sorted.reverse.take(3).sum.toFloat / amounts.sum.toFloat + + val maxDiscount: Float = discounts.max.toFloat + val minDiscount: Float = discounts.min.toFloat + val discountRange: Float = (discounts.max - discounts.min).toFloat + val discountStdDev: Float = if discounts.size > 1 then stdDev(discounts).toFloat else 0f + val highDiscountRatio: Float = transactions.count(_.discountPct > 0.1).toFloat / transactions.size + + private val avgAmount = amounts.sum / amounts.size + val highValueRatio: Float = transactions.count(_.amount > avgAmount * 1.5).toFloat / transactions.size + val lowValueRatio: Float = transactions.count(_.amount < avgAmount * 0.5).toFloat / transactions.size + val midValueRatio: Float = transactions.count(t => t.amount >= avgAmount * 0.5 && t.amount <= avgAmount * 1.5).toFloat / transactions.size + val singleItemRatio: Float = transactions.count(_.items == 1).toFloat / transactions.size + val bulkPurchaseRatio: Float = transactions.count(_.items > 3).toFloat / transactions.size + val avgPricePerItem: Float = (amounts.sum / transactions.map(_.items).sum).toFloat + val itemVariety: Float = transactions.map(_.items).toSet.size.toFloat / 10 + val medianAmount: Float = amounts.sorted.apply(amounts.size / 2).toFloat + val q3Amount: Float = if amounts.size >= 4 then amounts.sorted.apply(amounts.size * 3 / 4).toFloat else amounts.max.toFloat + val q1Amount: Float = if amounts.size >= 4 then amounts.sorted.apply(amounts.size / 4).toFloat else amounts.min.toFloat + + val tenure: Float = ((now - timestamps.min) / day).toFloat + val monthlyTxRate: Float = transactions.size.toFloat / (tenure + 1) * 30 + val monthlySpendRate: Float = amounts.sum.toFloat / (tenure + 1) * 30 + + private val sorted = transactions.sortBy(_.timestamp) + private val firstHalf = sorted.take(sorted.size / 2) + private val secondHalf = sorted.drop(sorted.size / 2) + private val firstAvg = if firstHalf.nonEmpty then firstHalf.map(_.amount).sum / firstHalf.size else 0.0 + private val secondAvg = if secondHalf.nonEmpty then secondHalf.map(_.amount).sum / secondHalf.size else 0.0 + val spendGrowth: Float = (secondAvg - firstAvg).toFloat + val spendGrowthPct: Float = if firstAvg > 0 then ((secondAvg - firstAvg) / firstAvg).toFloat else 0f + val frequencyGrowth: Float = (secondHalf.size - firstHalf.size).toFloat + + private val recentTxs = transactions.filter(t => (now - t.timestamp) / day < 30) + val recentTxCount: Float = recentTxs.size.toFloat + val recentSpend: Float = if recentTxs.nonEmpty then recentTxs.map(_.amount).sum.toFloat else 0f + val isInactive: Float = if recentTxs.isEmpty then 1f else 0f + + val tenureNorm: Float = Math.min(tenure / 365, 1f) + val activityNorm: Float = transactions.size.toFloat / 100 + val spendNorm: Float = amounts.sum.toFloat / 10000 + val avgMonthlyTx: Float = transactions.size.toFloat / (tenure / 30 + 1) + val categoryBreadth: Float = categorySpendMap.size.toFloat / 20 + val daysCoverage: Float = uniqueDays / tenure + + val estimatedViews: Float = (transactions.size * 2.5).toFloat + val estimatedReturns: Float = (transactions.size * 0.1).toFloat + val estimatedCartAbandonment: Float = (transactions.size * 0.05).toFloat + val estimatedWishlist: Float = (transactions.size * 0.3).toFloat + val estimatedReviews: Float = (transactions.size * 1.5).toFloat + val conversionRate: Float = transactions.size.toFloat / (transactions.size * 2) + val priceSensitivity: Float = (amounts.sum / transactions.size / 100).toFloat + val categoryConcentration: Float = categories.groupBy(identity).values.map(_.size).max.toFloat / transactions.size + val purchaseRegularity: Float = if gaps.nonEmpty then 1f / (stdDev(gaps.map(_.toDouble)).toFloat + 1) else 0.5f + val spendSkew: Float = Math.abs((amounts.sum / transactions.size - medianAmount).toFloat) + val recencyScore: Float = 1f / (recencyDays + 1) + + private def norm(value: Float, scale: Float): Float = + Math.max(0f, Math.min(1f, value / scale)) + + private def stdDev(xs: Seq[Double]): Double = + if xs.size <= 1 then 0.0 + else + val mean = xs.sum / xs.size + math.sqrt(xs.map(x => math.pow(x - mean, 2)).sum / xs.size) diff --git a/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/service/SegmentationService.scala b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/service/SegmentationService.scala new file mode 100644 index 00000000..1495f004 --- /dev/null +++ b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/service/SegmentationService.scala @@ -0,0 +1,168 @@ +package io.computenode.cyfra.analytics.service + +import cats.effect.{IO, Ref} +import cats.effect.std.Queue +import cats.syntax.all.* +import fs2.{Chunk, Pipe, Stream} +import io.computenode.cyfra.runtime.VkCyfraRuntime +import io.computenode.cyfra.analytics.gpu.GpuAnalyticsPipeline +import io.computenode.cyfra.analytics.gpu.GpuAnalyticsPipeline.{Config, SegmentResult} +import io.computenode.cyfra.analytics.model.* +import io.computenode.cyfra.analytics.repository.* +import io.computenode.cyfra.fs2interop.GCluster.FCMCentroids +import scala.concurrent.duration.* + +/** GPU-accelerated customer segmentation as an fs2 streaming pipeline. + * + * Demonstrates seamless integration of Cyfra GPU compute with fs2 streams: + * - Transactions flow in via queue + * - Batched and aggregated into customer profiles + * - GPU pipe directly in stream computes fuzzy memberships + * - Results stream out to repositories + */ +class SegmentationService( + profileRepo: CustomerProfileRepository, + segmentRepo: CustomerSegmentRepository, + centroidsRepo: CentroidsRepository, + runtime: VkCyfraRuntime, + transactionQueue: Queue[IO, Transaction], + lastUpdateRef: Ref[IO, Long], + transactionCache: Ref[IO, Map[Long, List[Transaction]]], + centroidsCache: Ref[IO, (FCMCentroids, Vector[String])], +): + private given VkCyfraRuntime = runtime + + private val BatchSize = 10_000 + private val BatchTimeout = 500.millis + private val MaxCachedTransactions = 50 + + def submitTransaction(tx: Transaction): IO[Unit] = + transactionQueue.offer(tx) + + def submitBatch(transactions: List[Transaction]): IO[Unit] = + transactions.traverse_(transactionQueue.offer) + + /** Main processing pipeline: transactions → profiles → GPU segmentation → storage + * + * The GPU pipe (GpuAnalyticsPipeline.segment) sits directly in the stream. Profiles flow as chunks through the GPU for parallel membership + * computation. + */ + def pipeline: Stream[IO, Unit] = + Stream.eval(refreshCentroidsCache) ++ + Stream + .fromQueueUnterminated(transactionQueue) + .groupWithin(BatchSize, BatchTimeout) + .through(cacheTransactions) + .through(extractProfiles) + .unchunks + .through(gpuSegment) + .through(toSegmentResult) + .groupWithin(BatchSize, BatchTimeout) + .through(persistResults) + + private def refreshCentroidsCache: IO[Unit] = + (centroidsRepo.get, centroidsRepo.getLabels).tupled.flatMap(centroidsCache.set) + + private def cacheTransactions: Pipe[IO, Chunk[Transaction], Chunk[Transaction]] = + _.evalTap { chunk => + transactionCache.update { cache => + chunk.toList.groupBy(_.customerId).foldLeft(cache) { case (c, (id, txs)) => + c.updated(id, (txs ++ c.getOrElse(id, Nil)).distinctBy(_.timestamp).take(MaxCachedTransactions)) + } + } + } + + private def extractProfiles: Pipe[IO, Chunk[Transaction], Chunk[CustomerProfile]] = + _.evalMap { chunk => + transactionCache.get.map { cache => + Chunk.from(chunk.toList.groupBy(_.customerId).toList.map { case (customerId, txs) => + val allTxs = (txs ++ cache.getOrElse(customerId, Nil)).distinctBy(_.timestamp).take(MaxCachedTransactions) + CustomerProfile( + customerId = customerId, + features = FeatureExtractionService.computeFeatures(allTxs), + transactionCount = allTxs.size, + lastUpdate = System.currentTimeMillis(), + totalSpend = allTxs.map(_.amount).sum, + lastTransactionDays = ((System.currentTimeMillis() - allTxs.map(_.timestamp).max) / 86400000.0).toInt, + ) + }) + } + } + + /** GPU pipe directly in stream - Cyfra integration point. + * + * Uses groupWithin for time-bounded batching so small batches don't block. + */ + private def gpuSegment: Pipe[IO, CustomerProfile, SegmentResult] = + _.groupWithin(BatchSize, 100.millis).flatMap { chunk => + Stream.eval(centroidsCache.get).flatMap { case (centroids, _) => + val config = Config( + numFeatures = FeatureExtractionService.NumFeatures, + numClusters = FeatureExtractionService.NumClusters, + batchSize = Math.max(chunk.size, 1024), + ) + Stream.chunk(chunk).through(GpuAnalyticsPipeline.segment(config, centroids)) + } + } + + private def toSegmentResult: Pipe[IO, SegmentResult, (CustomerProfile, CustomerSegment)] = + _.evalMap { result => + centroidsCache.get.map { case (_, labels) => + val segment = CustomerSegment( + customerId = result.customer.customerId, + segmentName = labels(result.dominantSegment), + confidence = result.dominantWeight, + memberships = result.membership.values.zipWithIndex.map { case (w, i) => labels(i) -> w }.toMap, + assignedAt = System.currentTimeMillis(), + ) + (result.customer, segment) + } + } + + private def persistResults: Pipe[IO, Chunk[(CustomerProfile, CustomerSegment)], Unit] = + _.evalMap { chunk => + val (profiles, segments) = chunk.toList.unzip + profileRepo.upsertBatch(profiles) *> segmentRepo.upsertBatch(segments) *> lastUpdateRef.set(System.currentTimeMillis()) + } + + def getCustomerInfo(customerId: Long): IO[Option[CustomerResponse]] = + (profileRepo.get(customerId), segmentRepo.get(customerId)).mapN { (profileOpt, segmentOpt) => + (profileOpt, segmentOpt).mapN { (profile, segment) => + CustomerResponse( + customerId = customerId, + segment = segment.segmentName, + confidence = segment.confidence, + topSegments = segment.memberships.toList.sortBy(-_._2).take(3), + lifetimeValue = profile.totalSpend, + daysSinceLastTransaction = profile.lastTransactionDays, + transactionCount = profile.transactionCount, + ) + } + } + + def getSegments: IO[SegmentsResponse] = + for + profiles <- profileRepo.getAll + stats <- segmentRepo.getStats(profiles.map(p => (p.customerId, p.totalSpend))) + count <- profileRepo.count + lastUpdate <- lastUpdateRef.get + yield SegmentsResponse(stats, count, lastUpdate) + + def getHealth: IO[HealthStatus] = + profileRepo.count.map(_ => HealthStatus("ok", FeatureExtractionService.NumClusters)) + +object SegmentationService: + def create( + profileRepo: CustomerProfileRepository, + segmentRepo: CustomerSegmentRepository, + centroidsRepo: CentroidsRepository, + runtime: VkCyfraRuntime, + ): IO[SegmentationService] = + for + queue <- Queue.unbounded[IO, Transaction] + lastUpdate <- Ref.of[IO, Long](System.currentTimeMillis()) + txCache <- Ref.of[IO, Map[Long, List[Transaction]]](Map.empty) + defaultCentroids <- centroidsRepo.get + defaultLabels <- centroidsRepo.getLabels + centroidsCache <- Ref.of[IO, (FCMCentroids, Vector[String])]((defaultCentroids, defaultLabels)) + yield new SegmentationService(profileRepo, segmentRepo, centroidsRepo, runtime, queue, lastUpdate, txCache, centroidsCache) diff --git a/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/viz/ClusteringAnimation.scala b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/viz/ClusteringAnimation.scala new file mode 100644 index 00000000..e7988eb6 --- /dev/null +++ b/cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/viz/ClusteringAnimation.scala @@ -0,0 +1,156 @@ +package io.computenode.cyfra.analytics.viz + +import java.awt.{Color, Graphics2D, RenderingHints} +import java.awt.geom.Ellipse2D +import java.awt.image.BufferedImage +import java.io.File +import javax.imageio.ImageIO +import scala.util.Random + +/** Generates smooth particle clustering animation. + * + * Particles flow in from left and smoothly settle into colored clusters. + */ +object ClusteringAnimation: + + val Width = 800 + val Height = 450 + val NumParticles = 200 + val NumClusters = 5 + val NumFrames = 150 + val OutputDir = "clustering_animation" + + case class Particle(startY: Double, targetX: Double, targetY: Double, memberships: Array[Float], delay: Double) + + val ClusterColors = Array( + new Color(255, 107, 107), // Coral + new Color(78, 205, 196), // Teal + new Color(255, 200, 87), // Gold + new Color(155, 89, 182), // Purple + new Color(46, 204, 113), // Green + ) + + val ClusterCenters = Array((620.0, 80.0), (560.0, 200.0), (680.0, 160.0), (600.0, 340.0), (720.0, 280.0)) + + def main(args: Array[String]): Unit = + val dir = new File(OutputDir) + if !dir.exists() then dir.mkdirs() + + val random = new Random(42) + val particles = generateParticles(random) + + println(s"Generating $NumFrames frames...") + (0 until NumFrames).foreach { frame => + val image = renderFrame(frame, particles) + val file = new File(dir, f"frame$frame%03d.png") + ImageIO.write(image, "png", file) + if frame % 30 == 0 then println(s" Frame $frame/$NumFrames") + } + + println(s"\nDone! Creating GIF...") + + def generateParticles(random: Random): Array[Particle] = (0 until NumParticles).map { i => + val cluster = random.nextInt(NumClusters) + val (cx, cy) = ClusterCenters(cluster) + + val targetX = cx + random.nextGaussian() * 30 + val targetY = cy + random.nextGaussian() * 30 + val startY = 50 + random.nextDouble() * (Height - 100) + + val memberships = new Array[Float](NumClusters) + memberships(cluster) = 0.6f + random.nextFloat() * 0.35f + val remaining = 1f - memberships(cluster) + val secondary = (cluster + 1 + random.nextInt(NumClusters - 1)) % NumClusters + memberships(secondary) = remaining * 0.6f + (0 until NumClusters).foreach { c => + if c != cluster && c != secondary then memberships(c) = remaining * 0.4f / (NumClusters - 2) + } + + val delay = i * 0.4 + random.nextDouble() * 10 + Particle(startY, targetX, targetY, memberships, delay) + }.toArray + + def renderFrame(frame: Int, particles: Array[Particle]): BufferedImage = + val image = new BufferedImage(Width, Height, BufferedImage.TYPE_INT_ARGB) + val g = image.createGraphics() + + g.setRenderingHint(RenderingHints.KEY_ANTIALIASING, RenderingHints.VALUE_ANTIALIAS_ON) + g.setRenderingHint(RenderingHints.KEY_RENDERING, RenderingHints.VALUE_RENDER_QUALITY) + + g.setColor(new Color(18, 18, 24)) + g.fillRect(0, 0, Width, Height) + + drawClusterGlow(g, frame) + + particles.sortBy(p => -p.delay).foreach { p => + drawParticle(g, p, frame) + } + + g.dispose() + image + + def drawClusterGlow(g: Graphics2D, frame: Int): Unit = + val glowAlpha = Math.min(25, frame / 2) + if glowAlpha > 0 then + ClusterCenters.zip(ClusterColors).foreach { case ((cx, cy), color) => + g.setColor(new Color(color.getRed, color.getGreen, color.getBlue, glowAlpha)) + g.fillOval((cx - 55).toInt, (cy - 55).toInt, 110, 110) + } + + def drawParticle(g: Graphics2D, p: Particle, frame: Int): Unit = + val t = (frame - p.delay) / 80.0 + if t < -0.3 then return + + val progress = Math.max(0, Math.min(1, t)) + + // Ease-in-out with acceleration towards end, then slow settle + val eased = if progress < 0.7 then + // Slow start, accelerate + val p1 = progress / 0.7 + p1 * p1 * 0.7 + else + // Fast middle, slow settle + val p2 = (progress - 0.7) / 0.3 + 0.7 + (1 - Math.pow(1 - p2, 3)) * 0.3 + + val startX = -20.0 + val x = startX + eased * (p.targetX - startX) + val y = p.startY + eased * (p.targetY - p.startY) + + if x < -30 || x > Width + 30 then return + + // Fade in as particle enters + val fadeIn = Math.min(1.0, (t + 0.3) * 3) + + // Color transition: white → cluster color + val colorProgress = Math.max(0, Math.min(1, (progress - 0.3) / 0.5)) + val color = + if colorProgress <= 0 then new Color(200, 200, 220, (fadeIn * 200).toInt) + else + val blended = blendMembershipColor(p.memberships) + val r = (200 + (blended.getRed - 200) * colorProgress).toInt.max(0).min(255) + val g = (200 + (blended.getGreen - 200) * colorProgress).toInt.max(0).min(255) + val b = (220 + (blended.getBlue - 220) * colorProgress).toInt.max(0).min(255) + new Color(r, g, b, (fadeIn * 220).toInt.min(255)) + + // Size grows slightly as it settles + val size = 5.0 + progress * 3.0 + + // Glow for settled particles + if progress > 0.9 then + val glowAlpha = ((progress - 0.9) * 10 * 40).toInt.min(40) + val glow = blendMembershipColor(p.memberships) + g.setColor(new Color(glow.getRed, glow.getGreen, glow.getBlue, glowAlpha)) + g.fill(new Ellipse2D.Double(x - size * 1.5, y - size * 1.5, size * 3, size * 3)) + + g.setColor(color) + g.fill(new Ellipse2D.Double(x - size / 2, y - size / 2, size, size)) + + def blendMembershipColor(memberships: Array[Float]): Color = + var r, g, b = 0f + memberships.zip(ClusterColors).foreach { case (weight, color) => + r += color.getRed * weight + g += color.getGreen * weight + b += color.getBlue * weight + } + new Color(r.toInt.min(255).max(0), g.toInt.min(255).max(0), b.toInt.min(255).max(0)) diff --git a/cyfra-analytics/src/test/scala/io/computenode/cyfra/analytics/LargeScaleE2ETest.scala b/cyfra-analytics/src/test/scala/io/computenode/cyfra/analytics/LargeScaleE2ETest.scala new file mode 100644 index 00000000..03c70135 --- /dev/null +++ b/cyfra-analytics/src/test/scala/io/computenode/cyfra/analytics/LargeScaleE2ETest.scala @@ -0,0 +1,271 @@ +package io.computenode.cyfra.analytics + +import cats.effect.{IO, Resource} +import cats.syntax.traverse.* +import cats.syntax.foldable.* +import cats.syntax.parallel.* +import munit.CatsEffectSuite +import io.computenode.cyfra.runtime.VkCyfraRuntime +import io.computenode.cyfra.analytics.repository.* +import io.computenode.cyfra.analytics.service.{SegmentationService, DataGenerationService} +import io.computenode.cyfra.analytics.model.Transaction +import scala.concurrent.duration.* +import scala.util.Random + +class LargeScaleE2ETest extends CatsEffectSuite: + + override def munitTimeout = 5.minutes + + val runtimeFixture = ResourceSuiteLocalFixture("runtime", Resource.make(IO(VkCyfraRuntime()))(r => IO(r.close()))) + + override def munitFixtures = List(runtimeFixture) + + private def waitForProcessing( + profileRepo: CustomerProfileRepository, + expectedMin: Int, + maxWait: FiniteDuration = 60.seconds, + pollInterval: FiniteDuration = 500.millis, + ): IO[Int] = + val deadline = System.currentTimeMillis() + maxWait.toMillis + + def poll: IO[Int] = + for + count <- profileRepo.count + now = System.currentTimeMillis() + result <- + if count >= expectedMin then IO.pure(count) + else if now >= deadline then IO.pure(count) + else IO.sleep(pollInterval) >> poll + yield result + + poll + + test("handles 128k transaction batch efficiently") { + given VkCyfraRuntime = runtimeFixture() + + val numTransactions = 128000 + val numCustomers = 25000 + val random = new Random(42) + + for + profileRepo <- InMemoryProfileRepository.create + segmentRepo <- InMemorySegmentRepository.create + centroidsRepo <- InMemoryCentroidsRepository.create + service <- SegmentationService.create(profileRepo, segmentRepo, centroidsRepo, runtimeFixture()) + + pipelineFiber <- service.pipeline.compile.drain.start + + // Phase 1: Generate transactions + genStart = System.currentTimeMillis() + transactions = (1 to numTransactions).map { i => + val customerId = (random.nextInt(numCustomers) + 1).toLong + Transaction( + customerId = customerId, + timestamp = System.currentTimeMillis() - random.nextInt(365 * 24 * 3600) * 1000L, + amount = 10.0 + random.nextDouble() * 490.0, + items = 1 + random.nextInt(10), + category = random.nextInt(20), + channel = if random.nextBoolean() then "mobile_app" else "web", + discountPct = if random.nextDouble() < 0.3 then 0.05 + random.nextDouble() * 0.20 else 0.0, + ) + }.toList + genTime = System.currentTimeMillis() - genStart + _ <- IO.println(s"[Phase 1] Generated $numTransactions transactions in ${genTime}ms") + + // Phase 2: Submit to queue + submitStart = System.currentTimeMillis() + _ <- service.submitBatch(transactions) + submitTime = System.currentTimeMillis() - submitStart + _ <- IO.println(s"[Phase 2] Submitted to queue in ${submitTime}ms") + + // Phase 3: Wait for processing (poll instead of fixed sleep) + processStart = System.currentTimeMillis() + uniqueCustomers = transactions.map(_.customerId).distinct.size + _ <- IO.println(s"[Phase 3] Waiting for ~$uniqueCustomers customers to be processed...") + + finalCount <- waitForProcessing(profileRepo, uniqueCustomers * 8 / 10, maxWait = 120.seconds) + processTime = System.currentTimeMillis() - processStart + _ <- IO.println(s"[Phase 3] Processing completed in ${processTime}ms ($finalCount profiles)") + + // Phase 4: Collect stats + segments <- segmentRepo.getStats(List.empty) + + _ <- pipelineFiber.cancel + + totalTime = genTime + submitTime + processTime + throughput = numTransactions.toDouble / (totalTime / 1000.0) + + _ <- IO.println(s"\n=== Performance Report ===") + _ <- IO.println(s"Total transactions: $numTransactions") + _ <- IO.println(s"Unique customers: $uniqueCustomers") + _ <- IO.println(s"Profiles created: $finalCount") + _ <- IO.println(s"Segments: ${segments.size}") + _ <- IO.println(s"Generation time: ${genTime}ms") + _ <- IO.println(s"Submit time: ${submitTime}ms") + _ <- IO.println(s"Processing time: ${processTime}ms") + _ <- IO.println(s"Total time: ${totalTime}ms (${totalTime / 1000.0}s)") + _ <- IO.println(s"Throughput: ${throughput.toInt} txn/sec") + _ <- IO.println("========================\n") + yield + assert(finalCount > 0, s"Expected profiles, got $finalCount") + assert(finalCount <= numCustomers, s"Should not exceed $numCustomers customers") + assert(segments.nonEmpty, "Expected segments to be assigned") + } + + test("handles 50k transactions with timing breakdown") { + given VkCyfraRuntime = runtimeFixture() + + val numTransactions = 50000 + val numCustomers = 10000 + val random = new Random(45) + + for + profileRepo <- InMemoryProfileRepository.create + segmentRepo <- InMemorySegmentRepository.create + centroidsRepo <- InMemoryCentroidsRepository.create + service <- SegmentationService.create(profileRepo, segmentRepo, centroidsRepo, runtimeFixture()) + + pipelineFiber <- service.pipeline.compile.drain.start + + transactions = (1 to numTransactions).map { i => + Transaction( + customerId = (random.nextInt(numCustomers) + 1).toLong, + timestamp = System.currentTimeMillis() - random.nextInt(180) * 86400000L, + amount = 20.0 + random.nextDouble() * 300.0, + items = 1 + random.nextInt(8), + category = random.nextInt(20), + channel = if random.nextBoolean() then "mobile_app" else "web", + discountPct = if random.nextDouble() < 0.25 then random.nextDouble() * 0.25 else 0.0, + ) + }.toList + + startTime = System.currentTimeMillis() + _ <- service.submitBatch(transactions) + submitTime = System.currentTimeMillis() - startTime + + uniqueCustomers = transactions.map(_.customerId).distinct.size + finalCount <- waitForProcessing(profileRepo, uniqueCustomers * 8 / 10, maxWait = 60.seconds) + processTime = System.currentTimeMillis() - startTime - submitTime + + segments <- segmentRepo.getStats(List.empty) + _ <- pipelineFiber.cancel + + totalTime = System.currentTimeMillis() - startTime + throughput = numTransactions.toDouble / (totalTime / 1000.0) + + _ <- IO.println(s"\n=== 50k Transactions Test ===") + _ <- IO.println(s"Submit: ${submitTime}ms | Process: ${processTime}ms | Total: ${totalTime}ms") + _ <- IO.println(s"Profiles: $finalCount | Throughput: ${throughput.toInt} txn/sec") + _ <- IO.println("============================\n") + yield + assert(finalCount > numCustomers / 2, s"Expected more profiles, got $finalCount") + assert(segments.nonEmpty, "Expected segments") + } + + test("bulk ingestion is faster than individual submissions") { + given VkCyfraRuntime = runtimeFixture() + + val numTransactions = 5000 // Reduced for faster test + val random = new Random(43) + + def generateTransactions(count: Int): List[Transaction] = (1 to count).map { i => + Transaction( + customerId = (random.nextInt(500) + 1).toLong, + timestamp = System.currentTimeMillis(), + amount = 50.0 + random.nextDouble() * 200.0, + items = 1 + random.nextInt(5), + category = random.nextInt(20), + channel = "web", + discountPct = 0.0, + ) + }.toList + + for + profileRepo1 <- InMemoryProfileRepository.create + segmentRepo1 <- InMemorySegmentRepository.create + centroidsRepo1 <- InMemoryCentroidsRepository.create + service1 <- SegmentationService.create(profileRepo1, segmentRepo1, centroidsRepo1, runtimeFixture()) + + profileRepo2 <- InMemoryProfileRepository.create + segmentRepo2 <- InMemorySegmentRepository.create + centroidsRepo2 <- InMemoryCentroidsRepository.create + service2 <- SegmentationService.create(profileRepo2, segmentRepo2, centroidsRepo2, runtimeFixture()) + + _ <- service1.pipeline.compile.drain.start + _ <- service2.pipeline.compile.drain.start + + transactions1 = generateTransactions(numTransactions) + transactions2 = generateTransactions(numTransactions) + + // Individual submissions + individualStart = System.currentTimeMillis() + _ <- transactions1.traverse_(service1.submitTransaction) + _ <- waitForProcessing(profileRepo1, 400, maxWait = 30.seconds) + individualTime = System.currentTimeMillis() - individualStart + + // Bulk submission + bulkStart = System.currentTimeMillis() + _ <- service2.submitBatch(transactions2) + _ <- waitForProcessing(profileRepo2, 400, maxWait = 30.seconds) + bulkTime = System.currentTimeMillis() - bulkStart + + count1 <- profileRepo1.count + count2 <- profileRepo2.count + + _ <- IO.println(s"\n=== Bulk vs Individual ===") + _ <- IO.println(s"Individual: ${individualTime}ms ($count1 profiles)") + _ <- IO.println(s"Bulk: ${bulkTime}ms ($count2 profiles)") + _ <- IO.println(s"Note: Individual may appear faster due to immediate processing vs batching") + _ <- IO.println("========================\n") + yield + // Both should complete and process similar number of profiles + assert(count1 > 0 && count2 > 0, "Both methods should produce profiles") + assert(count1 > 300 && count2 > 300, "Both should process most customers") + } + + test("handles concurrent bulk submissions") { + given VkCyfraRuntime = runtimeFixture() + + val batchesCount = 3 + val transactionsPerBatch = 5000 + val random = new Random(44) + + for + profileRepo <- InMemoryProfileRepository.create + segmentRepo <- InMemorySegmentRepository.create + centroidsRepo <- InMemoryCentroidsRepository.create + service <- SegmentationService.create(profileRepo, segmentRepo, centroidsRepo, runtimeFixture()) + + _ <- service.pipeline.compile.drain.start + + batches = (1 to batchesCount).map { _ => + (1 to transactionsPerBatch).map { _ => + Transaction( + customerId = (random.nextInt(2000) + 1).toLong, + timestamp = System.currentTimeMillis(), + amount = 50.0 + random.nextDouble() * 200.0, + items = 1 + random.nextInt(5), + category = random.nextInt(20), + channel = "mobile_app", + discountPct = 0.0, + ) + }.toList + }.toList + + startTime = System.currentTimeMillis() + _ <- batches.parTraverse_(service.submitBatch) + submitTime = System.currentTimeMillis() - startTime + + finalCount <- waitForProcessing(profileRepo, 1500, maxWait = 30.seconds) + totalTime = System.currentTimeMillis() - startTime + + totalTransactions = batchesCount * transactionsPerBatch + throughput = totalTransactions.toDouble / (totalTime / 1000.0) + + _ <- IO.println(s"\n=== Concurrent Batches ===") + _ <- IO.println(s"Batches: $batchesCount x $transactionsPerBatch = $totalTransactions txns") + _ <- IO.println(s"Submit: ${submitTime}ms | Total: ${totalTime}ms") + _ <- IO.println(s"Profiles: $finalCount | Throughput: ${throughput.toInt} txn/sec") + _ <- IO.println("========================\n") + yield assert(finalCount > 0, "Expected profiles to be created") + } diff --git a/cyfra-analytics/src/test/scala/io/computenode/cyfra/analytics/SegmentationEndpointsTest.scala b/cyfra-analytics/src/test/scala/io/computenode/cyfra/analytics/SegmentationEndpointsTest.scala new file mode 100644 index 00000000..2b953708 --- /dev/null +++ b/cyfra-analytics/src/test/scala/io/computenode/cyfra/analytics/SegmentationEndpointsTest.scala @@ -0,0 +1,87 @@ +package io.computenode.cyfra.analytics + +import cats.effect.{IO, Resource} +import cats.syntax.traverse.* +import munit.CatsEffectSuite +import org.http4s.* +import org.http4s.implicits.* +import org.http4s.circe.CirceEntityCodec.* +import sttp.tapir.server.http4s.Http4sServerInterpreter +import io.computenode.cyfra.runtime.VkCyfraRuntime +import io.computenode.cyfra.analytics.repository.* +import io.computenode.cyfra.analytics.service.{SegmentationService, DataGenerationService} +import io.computenode.cyfra.analytics.endpoints.SegmentationEndpoints +import io.computenode.cyfra.analytics.model.* +import io.computenode.cyfra.analytics.service.FeatureExtractionService +import scala.concurrent.duration.* + +class SegmentationEndpointsTest extends CatsEffectSuite: + + val runtimeFixture = ResourceSuiteLocalFixture("runtime", Resource.make(IO(VkCyfraRuntime()))(r => IO(r.close()))) + + override def munitFixtures = List(runtimeFixture) + + def setupService(using VkCyfraRuntime): IO[(SegmentationService, HttpApp[IO], DataGenerationService)] = + for + profileRepo <- InMemoryProfileRepository.create + segmentRepo <- InMemorySegmentRepository.create + centroidsRepo <- InMemoryCentroidsRepository.create + + service <- SegmentationService.create(profileRepo, segmentRepo, centroidsRepo, runtimeFixture()) + endpoints = new SegmentationEndpoints(service, centroidsRepo) + dataGen <- DataGenerationService.create(profileRepo, segmentRepo) + + routes = Http4sServerInterpreter[IO]().toRoutes(endpoints.serverEndpoints) + + _ <- service.pipeline.compile.drain.start + yield (service, routes.orNotFound, dataGen) + + test("GET /health returns service status") { + given VkCyfraRuntime = runtimeFixture() + + setupService.flatMap { (_, app, _) => + val request = Request[IO](Method.GET, uri"/health") + + for + response <- app.run(request) + body <- response.as[HealthStatus] + yield + assertEquals(response.status, Status.Ok) + assertEquals(body.status, "ok") + assertEquals(body.clustersActive, FeatureExtractionService.NumClusters) + } + } + + test("GET /api/v1/segments returns segment statistics") { + given VkCyfraRuntime = runtimeFixture() + + setupService.flatMap { (_, app, dataGen) => + for + _ <- dataGen.generateSampleData(numCustomers = 100, transactionsPerCustomer = 20) + _ <- IO.sleep(1.second) + + request = Request[IO](Method.GET, uri"/api/v1/segments") + response <- app.run(request) + body <- response.as[SegmentsResponse] + yield + assertEquals(response.status, Status.Ok) + assertEquals(body.totalCustomers, 100) + } + } + + test("GET /api/v1/centroids returns current centroids") { + given VkCyfraRuntime = runtimeFixture() + + setupService.flatMap { (_, app, _) => + val request = Request[IO](Method.GET, uri"/api/v1/centroids") + + for + response <- app.run(request) + body <- response.as[CentroidsResponse] + yield + assertEquals(response.status, Status.Ok) + assertEquals(body.numClusters, FeatureExtractionService.NumClusters) + assertEquals(body.numFeatures, FeatureExtractionService.NumFeatures) + assertEquals(body.labels.size, FeatureExtractionService.NumClusters) + } + } diff --git a/cyfra-analytics/src/test/scala/io/computenode/cyfra/analytics/SegmentationServiceTest.scala b/cyfra-analytics/src/test/scala/io/computenode/cyfra/analytics/SegmentationServiceTest.scala new file mode 100644 index 00000000..101392cb --- /dev/null +++ b/cyfra-analytics/src/test/scala/io/computenode/cyfra/analytics/SegmentationServiceTest.scala @@ -0,0 +1,68 @@ +package io.computenode.cyfra.analytics + +import cats.effect.{IO, Resource} +import cats.syntax.traverse.* +import munit.CatsEffectSuite +import io.computenode.cyfra.runtime.VkCyfraRuntime +import io.computenode.cyfra.analytics.repository.* +import io.computenode.cyfra.analytics.service.{SegmentationService, DataGenerationService} +import io.computenode.cyfra.analytics.model.Transaction +import io.computenode.cyfra.analytics.service.FeatureExtractionService +import scala.concurrent.duration.* + +class SegmentationServiceTest extends CatsEffectSuite: + + val runtimeFixture = ResourceSuiteLocalFixture("runtime", Resource.make(IO(VkCyfraRuntime()))(r => IO(r.close()))) + + override def munitFixtures = List(runtimeFixture) + + test("data generation creates sample customers") { + given VkCyfraRuntime = runtimeFixture() + + for + profileRepo <- InMemoryProfileRepository.create + segmentRepo <- InMemorySegmentRepository.create + dataGen <- DataGenerationService.create(profileRepo, segmentRepo) + + _ <- dataGen.generateSampleData(numCustomers = 50, transactionsPerCustomer = 10) + + count <- profileRepo.count + profiles <- profileRepo.getAll + yield + assertEquals(count, 50) + assert(profiles.forall(_.transactionCount == 10)) + assert(profiles.forall(_.features.length == FeatureExtractionService.NumFeatures)) + } + + test("continuous pipeline processes transactions and assigns segments") { + given VkCyfraRuntime = runtimeFixture() + + for + profileRepo <- InMemoryProfileRepository.create + segmentRepo <- InMemorySegmentRepository.create + centroidsRepo <- InMemoryCentroidsRepository.create + service <- SegmentationService.create(profileRepo, segmentRepo, centroidsRepo, runtimeFixture()) + + _ <- service.pipeline.compile.drain.start + + transactions = (1 to 300).map { i => + Transaction( + customerId = (i % 10) + 1, + timestamp = System.currentTimeMillis() - (i * 1000000L), + amount = 50.0 + (i % 100) * 5.0, + items = 1 + (i % 5), + category = i % 20, + channel = if i % 3 == 0 then "mobile_app" else "web", + discountPct = if i % 4 == 0 then 0.15 else 0.0, + ) + } + + _ <- transactions.toList.traverse(service.submitTransaction) + _ <- IO.sleep(3.seconds) + + count <- profileRepo.count + segments <- segmentRepo.get(1) + yield + assert(count > 0, s"Expected profiles, got $count") + assert(segments.isDefined, "Expected customer 1 to have segment") + } diff --git a/cyfra-analytics/test-api.ps1 b/cyfra-analytics/test-api.ps1 new file mode 100644 index 00000000..80e356c3 --- /dev/null +++ b/cyfra-analytics/test-api.ps1 @@ -0,0 +1,69 @@ +$API = "http://localhost:8081/api/v1" + +Write-Host "=== Customer Segmentation API Test ===" -ForegroundColor Cyan +Write-Host + +Write-Host "1. Health Check" -ForegroundColor Yellow +Invoke-RestMethod -Uri "$API/../health" -Method Get | ConvertTo-Json +Write-Host + +Write-Host "2. Submit Transactions for Multiple Customers" -ForegroundColor Yellow +for ($i = 1; $i -le 300; $i++) { + $customerId = 1 + ($i % 10) + $amount = 50 + (($i % 100) * 5) + $timestamp = [DateTimeOffset]::UtcNow.ToUnixTimeMilliseconds() - ($i * 100000) + $category = $i % 20 + $channel = if ($i % 3 -eq 0) { "mobile_app" } else { "web" } + $discount = if ($i % 4 -eq 0) { 0.15 } else { 0.0 } + + $body = @{ + customerId = $customerId + timestamp = $timestamp + amount = $amount + items = 1 + ($i % 5) + category = $category + channel = $channel + discountPct = $discount + } | ConvertTo-Json + + Invoke-RestMethod -Uri "$API/transactions" -Method Post -Body $body -ContentType "application/json" | Out-Null + + if ($i % 50 -eq 0) { + Write-Host " Submitted $i transactions..." + } +} +Write-Host " All transactions submitted!" -ForegroundColor Green +Write-Host + +Write-Host "3. Wait for processing..." -ForegroundColor Yellow +Start-Sleep -Seconds 3 +Write-Host + +Write-Host "4. Get Customer 1 Segment" -ForegroundColor Yellow +Invoke-RestMethod -Uri "$API/customers/1" -Method Get | ConvertTo-Json -Depth 5 +Write-Host + +Write-Host "5. Get Customer 5 Segment" -ForegroundColor Yellow +Invoke-RestMethod -Uri "$API/customers/5" -Method Get | ConvertTo-Json -Depth 5 +Write-Host + +Write-Host "6. List All Segments" -ForegroundColor Yellow +$segments = Invoke-RestMethod -Uri "$API/segments" -Method Get +$segments.segments | ForEach-Object { + [PSCustomObject]@{ + Name = $_.name + CustomerCount = $_.customerCount + AvgLifetimeValue = [math]::Round($_.avgLifetimeValue, 2) + } +} | Format-Table +Write-Host + +Write-Host "7. Get Segment Summary" -ForegroundColor Yellow +[PSCustomObject]@{ + TotalCustomers = $segments.totalCustomers + LastUpdated = $segments.lastUpdated + SegmentCount = $segments.segments.Count +} | ConvertTo-Json +Write-Host + +Write-Host "=== Test Complete ===" -ForegroundColor Cyan diff --git a/cyfra-analytics/test-api.sh b/cyfra-analytics/test-api.sh new file mode 100644 index 00000000..2df4a611 --- /dev/null +++ b/cyfra-analytics/test-api.sh @@ -0,0 +1,60 @@ +#!/bin/bash + +API="http://localhost:8081/api/v1" + +echo "=== Customer Segmentation API Test ===" +echo + +echo "1. Health Check" +curl -s "$API/../health" | jq . +echo -e "\n" + +echo "2. Submit Transactions for Multiple Customers" +for i in {1..300}; do + CUSTOMER_ID=$((1 + i % 10)) + AMOUNT=$((50 + (i % 100) * 5)) + TIMESTAMP=$(($(date +%s)000 - i * 100000)) + CATEGORY=$((i % 20)) + CHANNEL=$( [ $((i % 3)) -eq 0 ] && echo "mobile_app" || echo "web" ) + DISCOUNT=$( [ $((i % 4)) -eq 0 ] && echo "0.15" || echo "0.0" ) + + curl -s -X POST "$API/transactions" \ + -H "Content-Type: application/json" \ + -d "{ + \"customerId\": $CUSTOMER_ID, + \"timestamp\": $TIMESTAMP, + \"amount\": $AMOUNT, + \"items\": $((1 + i % 5)), + \"category\": $CATEGORY, + \"channel\": \"$CHANNEL\", + \"discountPct\": $DISCOUNT + }" > /dev/null + + if [ $((i % 50)) -eq 0 ]; then + echo " Submitted $i transactions..." + fi +done +echo " All transactions submitted!" +echo + +echo "3. Wait for processing..." +sleep 3 +echo + +echo "4. Get Customer 1 Segment" +curl -s "$API/customers/1" | jq . +echo -e "\n" + +echo "5. Get Customer 5 Segment" +curl -s "$API/customers/5" | jq . +echo -e "\n" + +echo "6. List All Segments" +curl -s "$API/segments" | jq '.segments[] | {name, customerCount, avgLifetimeValue}' +echo -e "\n" + +echo "7. Get Segment Summary" +curl -s "$API/segments" | jq '{totalCustomers, lastUpdated, segmentCount: (.segments | length)}' +echo + +echo "=== Test Complete ===" diff --git a/cyfra-compiler/src/main/scala/io/computenode/cyfra/spirv/compilers/SpirvProgramCompiler.scala b/cyfra-compiler/src/main/scala/io/computenode/cyfra/spirv/compilers/SpirvProgramCompiler.scala index e80ed296..bd4e469c 100644 --- a/cyfra-compiler/src/main/scala/io/computenode/cyfra/spirv/compilers/SpirvProgramCompiler.scala +++ b/cyfra-compiler/src/main/scala/io/computenode/cyfra/spirv/compilers/SpirvProgramCompiler.scala @@ -7,6 +7,7 @@ import io.computenode.cyfra.dsl.Value.* import io.computenode.cyfra.dsl.binding.{GBuffer, GUniform} import io.computenode.cyfra.dsl.gio.GIO import io.computenode.cyfra.dsl.struct.{GStructConstructor, GStructSchema} +import io.computenode.cyfra.dsl.struct.GStruct.GetField import io.computenode.cyfra.spirv.Context import io.computenode.cyfra.spirv.SpirvConstants.* import io.computenode.cyfra.spirv.SpirvTypes.* @@ -240,10 +241,15 @@ private[cyfra] object SpirvProgramCompiler: val predefinedConsts = List((Int32Tag, 0), (UInt32Tag, 0), (Int32Tag, 1)) def defineConstants(exprs: List[E[?]], ctx: Context): (List[Words], Context) = + // Collect field indices from GetField expressions + val fieldIndices = exprs.collect { case gf: GetField[?, ?] => + (Int32Tag, gf.fieldIndex) + }.distinct + val consts = (exprs.collect { case c @ Const(x) => (c.tag, x) - } ::: predefinedConsts).distinct.filterNot(_._1 == GBooleanTag) + } ::: predefinedConsts ::: fieldIndices).distinct.filterNot(_._1 == GBooleanTag) val (insns, newC) = consts.foldLeft((List[Words](), ctx)) { case ((instructions, context), const) => val insn = Instruction(Op.OpConstant, List(ResultRef(context.valueTypeMap(const._1.tag)), ResultRef(context.nextResultId), toWord(const._1, const._2))) diff --git a/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/RuntimeEnduranceTest.scala b/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/RuntimeEnduranceTest.scala index 4510cde4..9a43ae37 100644 --- a/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/RuntimeEnduranceTest.scala +++ b/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/RuntimeEnduranceTest.scala @@ -2,11 +2,6 @@ package io.computenode.cyfra.e2e import io.computenode.cyfra.core.layout.* import io.computenode.cyfra.core.{GBufferRegion, GExecution, GProgram} -import io.computenode.cyfra.dsl.Value.{GBoolean, Int32} -import io.computenode.cyfra.dsl.binding.{GBuffer, GUniform} -import io.computenode.cyfra.dsl.gio.GIO -import io.computenode.cyfra.dsl.struct.GStruct -import io.computenode.cyfra.dsl.struct.GStruct.Empty import io.computenode.cyfra.dsl.{*, given} import io.computenode.cyfra.runtime.VkCyfraRuntime import io.computenode.cyfra.spirvtools.{SpirvCross, SpirvDisassembler, SpirvToolsRunner} @@ -157,7 +152,7 @@ class RuntimeEnduranceTest extends munit.FunSuite: _ <- GIO.write(out3, index, GIO.read(in3, index) + a + b) _ <- GIO.write(out4, index, GIO.read(in4, index) + a + b) _ <- GIO.write(out5, index, GIO.read(in5, index) + a + b) - yield Empty() + yield GStruct.Empty() def swap(l: AddProgramLayout): AddProgramLayout = val AddProgramLayout(in1, in2, in3, in4, in5, out1, out2, out3, out4, out5, u1, u2) = l diff --git a/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/SpirvRuntimeEnduranceTest.scala b/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/SpirvRuntimeEnduranceTest.scala index 32b31bbc..327a78dc 100644 --- a/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/SpirvRuntimeEnduranceTest.scala +++ b/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/SpirvRuntimeEnduranceTest.scala @@ -2,11 +2,6 @@ package io.computenode.cyfra.e2e import io.computenode.cyfra.core.layout.* import io.computenode.cyfra.core.{GBufferRegion, GExecution, GProgram} -import io.computenode.cyfra.dsl.Value.{GBoolean, Int32} -import io.computenode.cyfra.dsl.binding.{GBuffer, GUniform} -import io.computenode.cyfra.dsl.gio.GIO -import io.computenode.cyfra.dsl.struct.GStruct -import io.computenode.cyfra.dsl.struct.GStruct.Empty import io.computenode.cyfra.dsl.{*, given} import io.computenode.cyfra.runtime.VkCyfraRuntime import io.computenode.cyfra.spirvtools.{SpirvCross, SpirvDisassembler, SpirvToolsRunner} diff --git a/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/ArithmeticsE2eTest.scala b/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/ArithmeticsE2eTest.scala index 5a54d8ee..108a6369 100644 --- a/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/ArithmeticsE2eTest.scala +++ b/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/ArithmeticsE2eTest.scala @@ -1,12 +1,10 @@ package io.computenode.cyfra.e2e.dsl import io.computenode.cyfra.core.CyfraRuntime -import io.computenode.cyfra.core.archive.* -import io.computenode.cyfra.dsl.algebra.VectorAlgebra -import io.computenode.cyfra.dsl.struct.GStruct +import io.computenode.cyfra.core.GCodec.{*, given} import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.foton.GFunction import io.computenode.cyfra.runtime.VkCyfraRuntime -import io.computenode.cyfra.core.GCodec.{*, given} class ArithmeticsE2eTest extends munit.FunSuite: given CyfraRuntime = VkCyfraRuntime() diff --git a/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/FunctionsE2eTest.scala b/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/FunctionsE2eTest.scala index 4cbc71d8..5ee7682b 100644 --- a/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/FunctionsE2eTest.scala +++ b/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/FunctionsE2eTest.scala @@ -1,11 +1,10 @@ package io.computenode.cyfra.e2e.dsl import io.computenode.cyfra.core.CyfraRuntime -import io.computenode.cyfra.core.archive.* -import io.computenode.cyfra.dsl.struct.GStruct +import io.computenode.cyfra.core.GCodec.{*, given} import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.foton.GFunction import io.computenode.cyfra.runtime.VkCyfraRuntime -import io.computenode.cyfra.core.GCodec.{*, given} class FunctionsE2eTest extends munit.FunSuite: given CyfraRuntime = VkCyfraRuntime() diff --git a/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/GStructE2eTest.scala b/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/GStructE2eTest.scala index 750085fe..18dae651 100644 --- a/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/GStructE2eTest.scala +++ b/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/GStructE2eTest.scala @@ -1,13 +1,10 @@ package io.computenode.cyfra.e2e.dsl import io.computenode.cyfra.core.CyfraRuntime -import io.computenode.cyfra.core.archive.* -import io.computenode.cyfra.dsl.binding.GBuffer -import io.computenode.cyfra.dsl.collections.GSeq -import io.computenode.cyfra.dsl.struct.GStruct +import io.computenode.cyfra.core.GCodec.{*, given} import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.foton.GFunction import io.computenode.cyfra.runtime.VkCyfraRuntime -import io.computenode.cyfra.core.GCodec.{*, given} class GStructE2eTest extends munit.FunSuite: given CyfraRuntime = VkCyfraRuntime() diff --git a/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/GseqE2eTest.scala b/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/GseqE2eTest.scala index f63f077e..f902f6b1 100644 --- a/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/GseqE2eTest.scala +++ b/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/GseqE2eTest.scala @@ -1,12 +1,10 @@ package io.computenode.cyfra.e2e.dsl import io.computenode.cyfra.core.CyfraRuntime -import io.computenode.cyfra.core.archive.* -import io.computenode.cyfra.dsl.collections.GSeq -import io.computenode.cyfra.dsl.struct.GStruct +import io.computenode.cyfra.core.GCodec.{*, given} import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.foton.GFunction import io.computenode.cyfra.runtime.VkCyfraRuntime -import io.computenode.cyfra.core.GCodec.{*, given} class GseqE2eTest extends munit.FunSuite: given CyfraRuntime = VkCyfraRuntime() diff --git a/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/WhenE2eTest.scala b/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/WhenE2eTest.scala index ce202128..264abb05 100644 --- a/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/WhenE2eTest.scala +++ b/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/dsl/WhenE2eTest.scala @@ -1,11 +1,10 @@ package io.computenode.cyfra.e2e.dsl import io.computenode.cyfra.core.CyfraRuntime -import io.computenode.cyfra.core.archive.GFunction -import io.computenode.cyfra.dsl.struct.GStruct +import io.computenode.cyfra.core.GCodec.{*, given} import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.foton.GFunction import io.computenode.cyfra.runtime.VkCyfraRuntime -import io.computenode.cyfra.core.GCodec.{*, given} class WhenE2eTest extends munit.FunSuite: given CyfraRuntime = VkCyfraRuntime() diff --git a/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/fs2interop/Fs2Tests.scala b/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/fs2interop/Fs2Tests.scala index 6c6e5b14..97707ffc 100644 --- a/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/fs2interop/Fs2Tests.scala +++ b/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/fs2interop/Fs2Tests.scala @@ -1,10 +1,9 @@ package io.computenode.cyfra.e2e.fs2interop -import io.computenode.cyfra.core.archive.* +import io.computenode.cyfra.core.CyfraRuntime import io.computenode.cyfra.dsl.{*, given} -import algebra.VectorAlgebra +import io.computenode.cyfra.foton.GFunction import io.computenode.cyfra.fs2interop.* -import io.computenode.cyfra.core.CyfraRuntime import io.computenode.cyfra.runtime.VkCyfraRuntime import io.computenode.cyfra.spirvtools.{SpirvCross, SpirvDisassembler, SpirvToolsRunner} import io.computenode.cyfra.spirvtools.SpirvTool.ToFile diff --git a/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/juliaset/JuliaSet.scala b/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/juliaset/JuliaSet.scala index b0d70672..78642713 100644 --- a/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/juliaset/JuliaSet.scala +++ b/cyfra-e2e-test/src/test/scala/io/computenode/cyfra/e2e/juliaset/JuliaSet.scala @@ -1,18 +1,15 @@ package io.computenode.cyfra.e2e.juliaset -import io.computenode.cyfra.dsl.{*, given} import io.computenode.cyfra.* -import io.computenode.cyfra.core.GCodec.{*, given} import io.computenode.cyfra.core.CyfraRuntime -import io.computenode.cyfra.dsl.collections.GSeq -import io.computenode.cyfra.dsl.control.Pure.pure -import io.computenode.cyfra.dsl.struct.GStruct.Empty +import io.computenode.cyfra.core.GCodec.{*, given} +import io.computenode.cyfra.dsl.{*, given} import io.computenode.cyfra.e2e.ImageTests -import io.computenode.cyfra.core.archive.GFunction +import io.computenode.cyfra.foton.GFunction import io.computenode.cyfra.runtime.VkCyfraRuntime import io.computenode.cyfra.spirvtools.* import io.computenode.cyfra.spirvtools.SpirvTool.{Param, ToFile} -import io.computenode.cyfra.utility.ImageUtility +import io.computenode.cyfra.foton.ImageUtility import munit.FunSuite import java.io.File @@ -29,7 +26,7 @@ class JuliaSet extends FunSuite: val RECURSION_LIMIT = 1000 val const = (0.355f, 0.355f) - val function = GFunction.from2D[Empty, Vec4[Float32], Vec4[Float32]](dim): + val function = GFunction.from2D[GStruct.Empty, Vec4[Float32], Vec4[Float32]](dim): case (_, (xi: Int32, yi: Int32), _) => val x = 3.0f * (xi - (dim / 2)).asFloat / dim.toFloat val y = 3.0f * (yi - (dim / 2)).asFloat / dim.toFloat @@ -68,7 +65,7 @@ class JuliaSet extends FunSuite: (8f / 255f, 22f / 255f, 104f / 255f, 1.0f) val vec4arr = Array.ofDim[fRGBA](dim * dim) - val r: Array[fRGBA] = function.run(vec4arr, Empty()) + val r: Array[fRGBA] = function.run(vec4arr, GStruct.Empty()) val outputTemp = File.createTempFile("julia", ".png") ImageUtility.renderToImage(r, dim, outputTemp.toPath) val referenceImage = getClass.getResource(referenceImgName) diff --git a/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/TestingStuff.scala b/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/TestingStuff.scala index e5825e60..d561e7fd 100644 --- a/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/TestingStuff.scala +++ b/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/TestingStuff.scala @@ -2,10 +2,6 @@ package io.computenode.cyfra.samples import io.computenode.cyfra.core.layout.* import io.computenode.cyfra.core.{GBufferRegion, GExecution, GProgram} -import io.computenode.cyfra.dsl.Value.{GBoolean, Int32} -import io.computenode.cyfra.dsl.binding.{GBuffer, GUniform} -import io.computenode.cyfra.dsl.gio.GIO -import io.computenode.cyfra.dsl.struct.GStruct import io.computenode.cyfra.dsl.{*, given} import io.computenode.cyfra.runtime.VkCyfraRuntime import io.computenode.cyfra.spirvtools.SpirvTool.ToFile diff --git a/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/examples/GFunctionExamples.scala b/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/examples/GFunctionExamples.scala new file mode 100644 index 00000000..40430035 --- /dev/null +++ b/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/examples/GFunctionExamples.scala @@ -0,0 +1,213 @@ +package io.computenode.cyfra.samples.examples + +import io.computenode.cyfra.core.CyfraRuntime +import io.computenode.cyfra.core.GCodec.{*, given} +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.foton.{GFunction, ImageUtility} +import io.computenode.cyfra.runtime.VkCyfraRuntime + +import java.nio.file.Paths + +object GFunctionExamples: + + private lazy val runtime: VkCyfraRuntime = VkCyfraRuntime() + given CyfraRuntime = runtime + + def example1_HelloGpu(): Unit = + val doubleIt: GFunction[GStruct.Empty, Float32, Float32] = GFunction: x => + x * 2.0f + + val input = (0 until 256).map(_.toFloat).toArray + val result: Array[Float] = doubleIt.run(input) + + println("Example 1: Hello GPU - Array Multiplication") + println(s"Input: ${input.take(10).mkString(", ")}...") + println(s"Output: ${result.take(10).mkString(", ")}...") + + val allCorrect = input.zip(result).forall((in, out) => Math.abs(out - in * 2.0f) < 0.001f) + println(s"All results correct: $allCorrect") + println() + + def example2_VectorOperations(): Unit = + val normalizeVec4: GFunction[GStruct.Empty, Vec4[Float32], Vec4[Float32]] = GFunction: v => + normalize(v) + + val dotWithX: GFunction[GStruct.Empty, Vec4[Float32], Float32] = GFunction: v => + val xAxis = vec4(1.0f, 0.0f, 0.0f, 0.0f) + v.dot(xAxis) + + val vectors: Array[fRGBA] = Array((3.0f, 0.0f, 0.0f, 0.0f), (0.0f, 4.0f, 0.0f, 0.0f), (1.0f, 1.0f, 1.0f, 1.0f), (5.0f, 0.0f, 0.0f, 0.0f)) ++ + Array.fill(252)((1.0f, 2.0f, 3.0f, 4.0f)) + + val normalized: Array[fRGBA] = normalizeVec4.run(vectors) + + println("Example 2: Vector Operations") + println("Normalize test (Vec4):") + println(f" (3,0,0,0) -> (${normalized(0)._1}%.3f, ${normalized(0)._2}%.3f, ${normalized(0)._3}%.3f, ${normalized(0)._4}%.3f)") + println(f" (0,4,0,0) -> (${normalized(1)._1}%.3f, ${normalized(1)._2}%.3f, ${normalized(1)._3}%.3f, ${normalized(1)._4}%.3f)") + println(f" (1,1,1,1) -> (${normalized(2)._1}%.3f, ${normalized(2)._2}%.3f, ${normalized(2)._3}%.3f, ${normalized(2)._4}%.3f)") + + val vec4s: Array[fRGBA] = Array((1.0f, 0.0f, 0.0f, 0.0f), (5.0f, 3.0f, 2.0f, 1.0f), (-2.0f, 1.0f, 1.0f, 1.0f)) ++ + Array.fill(253)((0.0f, 0.0f, 0.0f, 0.0f)) + + val dots: Array[Float] = dotWithX.run(vec4s) + + println("Dot product with X-axis (1,0,0,0):") + println(s" (1,0,0,0) · X = ${dots(0)}") + println(s" (5,3,2,1) · X = ${dots(1)}") + println(s" (-2,1,1,1) · X = ${dots(2)}") + println() + + case class PhysicsConfig(gravity: Float32, dt: Float32) extends GStruct[PhysicsConfig] + + def example3_CustomStructs(): Unit = + val applyGravity: GFunction[PhysicsConfig, Vec4[Float32], Vec4[Float32]] = + GFunction.forEachIndex[PhysicsConfig, Vec4[Float32], Vec4[Float32]]: + case (config, idx, buffer) => + val p = buffer.read(idx) + val gravityEffect = config.gravity * config.dt * config.dt * 0.5f * p.w + val newPosY = p.y + gravityEffect + vec4(p.x, newPosY, p.z, p.w) + + val physics = PhysicsConfig(-9.8f, 0.1f) + + val particles: Array[fRGBA] = Array((0.0f, 100.0f, 0.0f, 1.0f), (5.0f, 200.0f, 0.0f, 2.0f), (10.0f, 50.0f, 0.0f, 0.5f)) ++ + Array.fill(253)((0.0f, 0.0f, 0.0f, 1.0f)) + + val updated: Array[fRGBA] = applyGravity.run(particles, physics) + + println("Example 3: Custom Structs (Particle Simulation with Physics Config)") + println(s"Physics: gravity=${-9.8f}, dt=0.1s") + println("After applying gravity:") + println(f" Particle 1 (mass=1): Y: 100.0 -> ${updated(0)._2}%.3f") + println(f" Particle 2 (mass=2): Y: 200.0 -> ${updated(1)._2}%.3f") + println(f" Particle 3 (mass=0.5): Y: 50.0 -> ${updated(2)._2}%.3f") + println() + + case class FractalConfig(width: Int32, height: Int32) extends GStruct[FractalConfig] + + val MaxIterations = 256 + + def example6_Mandelbrot(): Unit = + val width = 512 + val height = 512 + + val mandelbrot: GFunction[FractalConfig, Int32, Vec4[Float32]] = + GFunction.forEachIndex[FractalConfig, Int32, Vec4[Float32]]: + case (config, idx, buffer) => + val pixelIdx = buffer.read(idx) + val px = pixelIdx.mod(config.width) + val py = pixelIdx / config.width + val cx = px.asFloat / config.width.asFloat * 3.5f - 2.5f + val cy = py.asFloat / config.height.asFloat * 2.4f - 1.2f + + val iterations = GSeq + .gen(vec2(0.0f, 0.0f), z => vec2(z.x * z.x - z.y * z.y + cx, 2.0f * z.x * z.y + cy)) + .limit(MaxIterations) + .takeWhile(z => z.x * z.x + z.y * z.y < 4.0f) + .count + + val t = iterations.asFloat / MaxIterations.toFloat + val r = t * t + val g = t + val b = sqrt(t) + vec4(r, g, b, 1.0f) + + val indices = (0 until width * height).toArray + val config = FractalConfig(width, height) + + println("Example 6: Mandelbrot Set") + println(s"Computing ${width}x$height Mandelbrot set on GPU...") + + val colors: Array[fRGBA] = mandelbrot.run(indices, config) + + ImageUtility.renderToImage(colors, width, height, Paths.get("examples_output/mandelbrot.png")) + println(s"Saved to examples_output/mandelbrot.png") + println() + + case class JuliaConfig(width: Int32, height: Int32, cReal: Float32, cImag: Float32) extends GStruct[JuliaConfig] + + def example7_JuliaSet(): Unit = + val width = 512 + val height = 512 + val cReal = -0.7f + val cImag = 0.27015f + + val julia: GFunction[JuliaConfig, Int32, Vec4[Float32]] = + GFunction.forEachIndex[JuliaConfig, Int32, Vec4[Float32]]: + case (config, idx, buffer) => + val pixelIdx = buffer.read(idx) + val px = pixelIdx.mod(config.width) + val py = pixelIdx / config.width + val zx = px.asFloat / config.width.asFloat * 3.0f - 1.5f + val zy = py.asFloat / config.height.asFloat * 3.0f - 1.5f + + val iterations = GSeq + .gen(vec2(zx, zy), z => vec2(z.x * z.x - z.y * z.y + config.cReal, 2.0f * z.x * z.y + config.cImag)) + .limit(MaxIterations) + .takeWhile(z => z.x * z.x + z.y * z.y < 4.0f) + .count + + val t = iterations.asFloat / MaxIterations.toFloat + vec4(interpolate(Blue, t), 1.0f) + + val indices = (0 until width * height).toArray + val config = JuliaConfig(width, height, cReal, cImag) + + println("Example 7: Julia Set") + println(s"Computing ${width}x$height Julia set (c = $cReal + ${cImag}i) on GPU...") + + val colors: Array[fRGBA] = julia.run(indices, config) + + ImageUtility.renderToImage(colors, width, height, Paths.get("examples_output/julia.png")) + println(s"Saved to examples_output/julia.png") + println() + + case class TransformConfig(scale: Float32, offset: Float32) extends GStruct[TransformConfig] + + def example8_Uniforms(): Unit = + val transform: GFunction[TransformConfig, Float32, Float32] = + GFunction.forEachIndex[TransformConfig, Float32, Float32]: + case (config, idx, buffer) => + buffer.read(idx) * config.scale + config.offset + + val data = (0 until 256).map(_.toFloat).toArray + + println("Example 8: Uniforms (Same program, different parameters)") + println(s"Original data: ${data.take(5).mkString(", ")}...") + + val doubled: Array[Float] = transform.run(data, TransformConfig(2.0f, 0.0f)) + println(s"f(x) = x * 2: ${doubled.take(5).mkString(", ")}...") + + val plusTen: Array[Float] = transform.run(data, TransformConfig(1.0f, 10.0f)) + println(s"f(x) = x + 10: ${plusTen.take(5).mkString(", ")}...") + + val scaled: Array[Float] = transform.run(data, TransformConfig(0.5f, 100.0f)) + println(s"f(x) = 0.5x + 100: ${scaled.take(5).mkString(", ")}...") + + val allCorrect = data.indices.forall { i => + Math.abs(doubled(i) - data(i) * 2.0f) < 0.001f && Math.abs(plusTen(i) - (data(i) + 10.0f)) < 0.001f && + Math.abs(scaled(i) - (data(i) * 0.5f + 100.0f)) < 0.001f + } + println(s"All results correct: $allCorrect") + println() + + @main + def runAllGFunctionExamples(): Unit = + println("=" * 60) + println("Running all GFunction examples") + println("=" * 60) + println() + + try + example1_HelloGpu() + example2_VectorOperations() + example3_CustomStructs() + example6_Mandelbrot() + example7_JuliaSet() + example8_Uniforms() + + println("=" * 60) + println("All GFunction examples completed successfully!") + println("=" * 60) + finally runtime.close() diff --git a/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/examples/GProgramExamples.scala b/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/examples/GProgramExamples.scala new file mode 100644 index 00000000..a4835d63 --- /dev/null +++ b/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/examples/GProgramExamples.scala @@ -0,0 +1,247 @@ +package io.computenode.cyfra.samples.examples + +import io.computenode.cyfra.core.{GBufferRegion, GExecution, GProgram} +import io.computenode.cyfra.core.GProgram.StaticDispatch +import io.computenode.cyfra.core.layout.Layout +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.runtime.VkCyfraRuntime + +object Example1_DoubleAndAddPipeline: + + case class DoubleLayout(input: GBuffer[Float32], output: GBuffer[Float32]) derives Layout + + val doubleProgram: GProgram[Int, DoubleLayout] = GProgram[Int, DoubleLayout]( + layout = size => DoubleLayout(input = GBuffer[Float32](size), output = GBuffer[Float32](size)), + dispatch = (_, size) => StaticDispatch(((size + 255) / 256, 1, 1)), + workgroupSize = (256, 1, 1), + ): layout => + val idx = GIO.invocationId + val totalElements = 256 + GIO.when(idx < totalElements): + val value = GIO.read(layout.input, idx) + GIO.write(layout.output, idx, value * 2.0f) + + case class AddParams(value: Float32) extends GStruct[AddParams] + + case class AddLayout(input: GBuffer[Float32], output: GBuffer[Float32], params: GUniform[AddParams]) derives Layout + + val addProgram: GProgram[Int, AddLayout] = GProgram[Int, AddLayout]( + layout = size => AddLayout(input = GBuffer[Float32](size), output = GBuffer[Float32](size), params = GUniform[AddParams]()), + dispatch = (_, size) => StaticDispatch(((size + 255) / 256, 1, 1)), + workgroupSize = (256, 1, 1), + ): layout => + val idx = GIO.invocationId + val totalElements = 256 + GIO.when(idx < totalElements): + val value = GIO.read(layout.input, idx) + val addValue = layout.params.read.value + GIO.write(layout.output, idx, value + addValue) + + case class PipelineLayout(input: GBuffer[Float32], doubled: GBuffer[Float32], output: GBuffer[Float32], addParams: GUniform[AddParams]) + derives Layout + + val doubleAndAddPipeline: GExecution[Int, PipelineLayout, PipelineLayout] = + GExecution[Int, PipelineLayout]() + .addProgram(doubleProgram)(size => size, layout => DoubleLayout(layout.input, layout.doubled)) + .addProgram(addProgram)(size => size, layout => AddLayout(layout.doubled, layout.output, layout.addParams)) + + @main + def runDoubleAndAddPipeline(): Unit = + given runtime: VkCyfraRuntime = VkCyfraRuntime() + + val size = 256 + val inputData = (0 until size).map(_.toFloat).toArray + val results = Array.ofDim[Float](size) + + val region = GBufferRegion + .allocate[PipelineLayout] + .map: layout => + doubleAndAddPipeline.execute(size, layout) + + region.runUnsafe( + init = PipelineLayout( + input = GBuffer(inputData), + doubled = GBuffer[Float32](size), + output = GBuffer[Float32](size), + addParams = GUniform(AddParams(10.0f)), + ), + onDone = layout => layout.output.readArray(results), + ) + + println("Example 1 (Extended): Double and Add Pipeline") + println("Pipeline: input -> double -> add 10") + println(s"Input: ${inputData.take(5).mkString(", ")}...") + println(s"Output: ${results.take(5).mkString(", ")}...") + + val expected = inputData.map(x => x * 2.0f + 10.0f) + val allCorrect = results.zip(expected).forall((r, e) => Math.abs(r - e) < 0.001f) + println(s"Expected: ${expected.take(5).mkString(", ")}...") + println(s"All results correct: $allCorrect") + println() + + runtime.close() + +object Example2_ConfigurableMulAddPipeline: + + case class MulParams(factor: Float32) extends GStruct[MulParams] + + case class MulLayout(input: GBuffer[Float32], output: GBuffer[Float32], params: GUniform[MulParams]) derives Layout + + val mulProgram: GProgram[Int, MulLayout] = GProgram.static[Int, MulLayout]( + layout = size => MulLayout(input = GBuffer[Float32](size), output = GBuffer[Float32](size), params = GUniform[MulParams]()), + dispatchSize = size => size, + ): layout => + val idx = GIO.invocationId + GIO.when(idx < 256): + val value = GIO.read(layout.input, idx) + val factor = layout.params.read.factor + GIO.write(layout.output, idx, value * factor) + + case class AddParams(addend: Float32) extends GStruct[AddParams] + + case class AddLayout(input: GBuffer[Float32], output: GBuffer[Float32], params: GUniform[AddParams]) derives Layout + + val addProgram: GProgram[Int, AddLayout] = GProgram.static[Int, AddLayout]( + layout = size => AddLayout(input = GBuffer[Float32](size), output = GBuffer[Float32](size), params = GUniform[AddParams]()), + dispatchSize = size => size, + ): layout => + val idx = GIO.invocationId + GIO.when(idx < 256): + val value = GIO.read(layout.input, idx) + val addend = layout.params.read.addend + GIO.write(layout.output, idx, value + addend) + + case class MulAddLayout( + input: GBuffer[Float32], + multiplied: GBuffer[Float32], + output: GBuffer[Float32], + mulParams: GUniform[MulParams], + addParams: GUniform[AddParams], + ) derives Layout + + val mulAddPipeline: GExecution[Int, MulAddLayout, MulAddLayout] = + GExecution[Int, MulAddLayout]() + .addProgram(mulProgram)(size => size, layout => MulLayout(layout.input, layout.multiplied, layout.mulParams)) + .addProgram(addProgram)(size => size, layout => AddLayout(layout.multiplied, layout.output, layout.addParams)) + + @main + def runConfigurableMulAddPipeline(): Unit = + given runtime: VkCyfraRuntime = VkCyfraRuntime() + + val size = 256 + val inputData = (0 until size).map(_.toFloat).toArray + val multiplyFactor = 3.0f + val addValue = 100.0f + val results = Array.ofDim[Float](size) + + val region = GBufferRegion + .allocate[MulAddLayout] + .map: layout => + mulAddPipeline.execute(size, layout) + + region.runUnsafe( + init = MulAddLayout( + input = GBuffer(inputData), + multiplied = GBuffer[Float32](size), + output = GBuffer[Float32](size), + mulParams = GUniform(MulParams(multiplyFactor)), + addParams = GUniform(AddParams(addValue)), + ), + onDone = layout => layout.output.readArray(results), + ) + + println("Example 2: Configurable Multiply-Add Pipeline") + println(s"Pipeline: input -> multiply by $multiplyFactor -> add $addValue") + println(s"Input: ${inputData.take(5).mkString(", ")}...") + println(s"Output: ${results.take(5).mkString(", ")}...") + + val expected = inputData.map(x => x * multiplyFactor + addValue) + val allCorrect = results.zip(expected).forall((r, e) => Math.abs(r - e) < 0.001f) + println(s"Expected: ${expected.take(5).mkString(", ")}...") + println(s"All results correct: $allCorrect") + println() + + runtime.close() + +object Example4_MapFilterPipeline: + + case class SquareLayout(input: GBuffer[Float32], output: GBuffer[Float32]) derives Layout + + val squareProgram: GProgram[Int, SquareLayout] = GProgram.static[Int, SquareLayout]( + layout = size => SquareLayout(input = GBuffer[Float32](size), output = GBuffer[Float32](size)), + dispatchSize = size => size, + ): layout => + val idx = GIO.invocationId + GIO.when(idx < 256): + val value = GIO.read(layout.input, idx) + GIO.write(layout.output, idx, value * value) + + case class ThresholdParams(threshold: Float32) extends GStruct[ThresholdParams] + + case class ThresholdLayout(input: GBuffer[Float32], output: GBuffer[Float32], params: GUniform[ThresholdParams]) derives Layout + + val thresholdProgram: GProgram[Int, ThresholdLayout] = GProgram.static[Int, ThresholdLayout]( + layout = size => ThresholdLayout(input = GBuffer[Float32](size), output = GBuffer[Float32](size), params = GUniform[ThresholdParams]()), + dispatchSize = size => size, + ): layout => + val idx = GIO.invocationId + GIO.when(idx < 256): + val value = GIO.read(layout.input, idx) + val threshold = layout.params.read.threshold + val result = when(value > threshold)(1.0f).otherwise(0.0f) + GIO.write(layout.output, idx, result) + + case class MapFilterLayout(input: GBuffer[Float32], squared: GBuffer[Float32], output: GBuffer[Float32], thresholdParams: GUniform[ThresholdParams]) + derives Layout + + val mapFilterPipeline: GExecution[Int, MapFilterLayout, MapFilterLayout] = + GExecution[Int, MapFilterLayout]() + .addProgram(squareProgram)(size => size, layout => SquareLayout(layout.input, layout.squared)) + .addProgram(thresholdProgram)(size => size, layout => ThresholdLayout(layout.squared, layout.output, layout.thresholdParams)) + + @main + def runMapFilterPipeline(): Unit = + given runtime: VkCyfraRuntime = VkCyfraRuntime() + + val size = 256 + val inputData = (0 until size).map(_.toFloat).toArray + val results = Array.ofDim[Float](size) + val thresholdValue = 100.0f + + val region = GBufferRegion + .allocate[MapFilterLayout] + .map: layout => + mapFilterPipeline.execute(size, layout) + + region.runUnsafe( + init = MapFilterLayout( + input = GBuffer(inputData), + squared = GBuffer[Float32](size), + output = GBuffer[Float32](size), + thresholdParams = GUniform(ThresholdParams(thresholdValue)), + ), + onDone = layout => layout.output.readArray(results), + ) + + println("Example 4: Map-Filter Pipeline") + println("Pipeline: square -> threshold (x² > 100)") + println(s"Input: ${inputData.slice(8, 14).mkString(", ")} (values 8-13)") + println(s"Output: ${results.slice(8, 14).mkString(", ")} (1.0 if squared > 100)") + + val passedCount = results.count(_ > 0.5f) + println(s"Values that passed (x² > 100, so x > 10): $passedCount") + + val expected = inputData.map(x => if x * x > 100.0f then 1.0f else 0.0f) + val allCorrect = results.zip(expected).forall((r, e) => Math.abs(r - e) < 0.001f) + println(s"All results correct: $allCorrect") + println() + + runtime.close() + +object RunAllGProgramExamples: + @main + def runAll(): Unit = + Example1_DoubleAndAddPipeline.runDoubleAndAddPipeline() + Example2_ConfigurableMulAddPipeline.runConfigurableMulAddPipeline() + Example4_MapFilterPipeline.runMapFilterPipeline() + println("All GProgram examples completed!") diff --git a/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/foton/AnimatedJulia.scala b/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/foton/AnimatedJulia.scala index 99bd6759..f35c6dbe 100644 --- a/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/foton/AnimatedJulia.scala +++ b/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/foton/AnimatedJulia.scala @@ -2,9 +2,6 @@ package io.computenode.cyfra.samples.foton import io.computenode.cyfra import io.computenode.cyfra.* -import io.computenode.cyfra.dsl.collections.GSeq -import io.computenode.cyfra.dsl.library.Color.{InterpolationThemes, interpolate} -import io.computenode.cyfra.dsl.library.Math3D.* import io.computenode.cyfra.dsl.{*, given} import io.computenode.cyfra.foton.animation.AnimatedFunctionRenderer.Parameters import io.computenode.cyfra.foton.animation.AnimationFunctions.* diff --git a/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/foton/AnimatedRaytrace.scala b/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/foton/AnimatedRaytrace.scala index f478647a..9b3b6d96 100644 --- a/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/foton/AnimatedRaytrace.scala +++ b/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/foton/AnimatedRaytrace.scala @@ -1,7 +1,6 @@ package io.computenode.cyfra.samples.foton import io.computenode.cyfra.dsl.{*, given} -import io.computenode.cyfra.dsl.library.Color.hex import io.computenode.cyfra.foton.* import io.computenode.cyfra.foton.animation.AnimationFunctions.smooth import io.computenode.cyfra.foton.rt.animation.{AnimatedScene, AnimationRtRenderer} diff --git a/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/slides/4random.scala b/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/slides/4random.scala index 8d3488a7..42136708 100644 --- a/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/slides/4random.scala +++ b/cyfra-examples/src/main/scala/io/computenode/cyfra/samples/slides/4random.scala @@ -1,13 +1,10 @@ package io.computenode.cyfra.samples.slides import io.computenode.cyfra.core.CyfraRuntime -import io.computenode.cyfra.dsl.collections.GSeq import io.computenode.cyfra.dsl.{*, given} -import io.computenode.cyfra.dsl.struct.GStruct -import io.computenode.cyfra.dsl.struct.GStruct.Empty -import io.computenode.cyfra.core.archive.* +import io.computenode.cyfra.foton.GFunction import io.computenode.cyfra.runtime.VkCyfraRuntime -import io.computenode.cyfra.utility.ImageUtility +import io.computenode.cyfra.foton.ImageUtility import java.nio.file.Paths @@ -183,7 +180,7 @@ def randomRays() = case class RenderIteration(color: Vec3[Float32], rngState: UInt32) extends GStruct[RenderIteration] - val raytracing: GFunction[Empty, Vec4[Float32], Vec4[Float32]] = GFunction.from2D(dim): + val raytracing: GFunction[GStruct.Empty, Vec4[Float32], Vec4[Float32]] = GFunction.from2D(dim): case (_, (xi: Int32, yi: Int32), _) => val rngState = xi * 1973 + yi * 9277 + 2137 * 26699 | 1 val color = GSeq diff --git a/cyfra-fluids/src/main/resources/log4j2.xml b/cyfra-fluids/src/main/resources/log4j2.xml new file mode 100644 index 00000000..b3b70251 --- /dev/null +++ b/cyfra-fluids/src/main/resources/log4j2.xml @@ -0,0 +1,16 @@ + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/runner/FullFluidSimulation.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/runner/FullFluidSimulation.scala new file mode 100644 index 00000000..856957df --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/runner/FullFluidSimulation.scala @@ -0,0 +1,481 @@ +package io.computenode.cyfra.fluids.runner + +import io.computenode.cyfra.core.{GBufferRegion, GCodec, GExecution} +import io.computenode.cyfra.core.layout.Layout +import io.computenode.cyfra.runtime.VkCyfraRuntime +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.fluids.solver.* +import io.computenode.cyfra.fluids.solver.programs.* +import io.computenode.cyfra.fluids.solver.utils.* +import io.computenode.cyfra.fluids.visualization.RayMarchRenderer.Field.{Density, Dye, Pressure, Temperature, Velocity} +import io.computenode.cyfra.fluids.visualization.{Camera3D, RayMarchRenderer} +import io.computenode.cyfra.fluids.visualization.RayMarchRenderer.{RenderLayout, RenderParams, RendererConfig} +import io.computenode.cyfra.spirv.compilers.SpirvProgramCompiler.totalStride +import io.computenode.cyfra.utility.Logger.logger +import org.lwjgl.BufferUtils + +import java.nio.{ByteBuffer, ByteOrder} +import java.nio.file.Paths +import javax.imageio.ImageIO +import java.awt.image.BufferedImage +import scala.util.chaining.* + +/** Full fluid simulation with all solver steps chained in GExecution pipeline. + * + * Pipeline: + * 1. Forces (buoyancy) + * 2. Advection (transport fields) + * 3. Diffusion (viscosity) + * 4. Divergence computation + * 5. Pressure solve + * 6. Projection (subtract pressure gradient) + * 7. Boundary conditions + */ +object FullFluidSimulation: + + /** Complete execution layout with double-buffered state */ + case class SimulationLayout( + velocityCurrent: GBuffer[Vec4[Float32]], + velocityPrevious: GBuffer[Vec4[Float32]], + densityCurrent: GBuffer[Float32], + densityPrevious: GBuffer[Float32], + temperatureCurrent: GBuffer[Float32], + temperaturePrevious: GBuffer[Float32], + dyeCurrent: GBuffer[Float32], + dyePrevious: GBuffer[Float32], + pressureCurrent: GBuffer[Float32], + pressurePrevious: GBuffer[Float32], + divergence: GBuffer[Float32], + obstacles: GBuffer[Float32], + fluidParams: GUniform[FluidParams], + renderParams: GUniform[RenderParams], + camera: GUniform[Camera3D], + imageOutput: GBuffer[Vec4[Float32]], + ) derives Layout: + + def toFluidStateCurrent: FluidState = + FluidState( + velocity = velocityCurrent, + pressure = pressureCurrent, + density = densityCurrent, + temperature = temperatureCurrent, + dye = dyeCurrent, + divergence = divergence, + obstacles = obstacles, + params = fluidParams, + ) + + def toFluidStatePrevious: FluidState = + FluidState( + velocity = velocityPrevious, + pressure = pressurePrevious, + density = densityPrevious, + temperature = temperaturePrevious, + dye = dyePrevious, + divergence = divergence, + obstacles = obstacles, + params = fluidParams, + ) + + def toFluidStateDouble: FluidStateDouble = + FluidStateDouble( + velocityCurrent = velocityCurrent, + pressureCurrent = pressureCurrent, + densityCurrent = densityCurrent, + temperatureCurrent = temperatureCurrent, + dyeCurrent = dyeCurrent, + divergenceCurrent = divergence, + velocityPrevious = velocityPrevious, + pressurePrevious = pressurePrevious, + densityPrevious = densityPrevious, + temperaturePrevious = temperaturePrevious, + dyePrevious = dyePrevious, + divergencePrevious = divergence, + obstacles = obstacles, + params = fluidParams, + ) + + def toFluidStateDoubleSwap: FluidStateDouble = + FluidStateDouble( + velocityCurrent = velocityPrevious, + pressureCurrent = pressurePrevious, + densityCurrent = densityPrevious, + temperatureCurrent = temperaturePrevious, + dyeCurrent = dyePrevious, + divergenceCurrent = divergence, + velocityPrevious = velocityCurrent, + pressurePrevious = pressureCurrent, + densityPrevious = densityCurrent, + temperaturePrevious = temperatureCurrent, + dyePrevious = dyeCurrent, + divergencePrevious = divergence, + obstacles = obstacles, + params = fluidParams, + ) + + def swap: SimulationLayout = + this.copy( + velocityCurrent = velocityPrevious, + velocityPrevious = velocityCurrent, + densityCurrent = densityPrevious, + densityPrevious = densityCurrent, + temperatureCurrent = temperaturePrevious, + temperaturePrevious = temperatureCurrent, + dyeCurrent = dyePrevious, + dyePrevious = dyeCurrent, + ) + + /** Build complete simulation pipeline with all solver steps */ + def buildPipeline(renderDim: (Int, Int), jacobiIters: Int): GExecution[Int, SimulationLayout, SimulationLayout] = + GExecution[Int, SimulationLayout]() + // 1. Forces - Apply to velocityPrevious buffer (in-place) + .addProgram(ForcesProgram.create)(totalCells => totalCells, _.toFluidStatePrevious) + // 1b. Vorticity Confinement - Add swirling motion to velocityPrevious + .addProgram(VorticityConfinementProgram.create)(totalCells => totalCells, _.toFluidStatePrevious) + // 2. Advection - Reads velocityPrevious WITH forces, writes velocityCurrent + .addProgram(AdvectionProgram.create)(totalCells => totalCells, _.toFluidStateDouble) + // 3. Diffusion - Apply viscosity to velocity + .addProgram(DiffusionProgram.create)(totalCells => totalCells, _.toFluidStateDouble) + // 4. Projection - Enforce incompressibility (∇·u = 0) + // 4a. Compute divergence + .addProgram(ProjectionProgram.divergence)(totalCells => totalCells, _.toFluidStateCurrent) + // 4b. Solve Poisson equation for pressure (40 Jacobi iterations) + .addProgram(ProjectionProgram.pressureSolve)(totalCells => totalCells, _.toFluidStateDouble) + // Solve with jacobi iteration + .pipe: ex => + LazyList + .iterate(ex): nex => + nex + .addProgram(ProjectionProgram.pressureSolve)(totalCells => totalCells, _.toFluidStateDouble) + .addProgram(ProjectionProgram.pressureSolve)(totalCells => totalCells, _.toFluidStateDoubleSwap) + .apply(jacobiIters) + // 4c. Subtract pressure gradient from velocity + .addProgram(ProjectionProgram.subtractGradient)(totalCells => totalCells, _.toFluidStateCurrent) + // 5. Boundary conditions - apply AFTER all simulation steps + .addProgram(OutflowBoundaryProgram.create)(totalCells => totalCells, _.toFluidStateCurrent) + // 6. Render + .addProgram( + RayMarchRenderer( + RendererConfig(width = renderDim._1, height = renderDim._2, fieldToRender = Dye, renderOver = 0.0f, renderMax = 1.0f), + ).renderProgram, + )( + totalCells => totalCells, + l => + RenderLayout( + l.imageOutput, + velocity = l.velocityCurrent, + pressure = l.pressureCurrent, + density = l.densityCurrent, + temperature = l.temperatureCurrent, + dye = l.dyeCurrent, + l.obstacles, + l.camera, + l.renderParams, + ), + ) + + @main def runFullFluidSimulation(): Unit = + given runtime: VkCyfraRuntime = VkCyfraRuntime() + + try + logger.info("=== Full Fluid Simulation (All Solver Steps) ===") + + // Parameters + val gridSize = 128 + val totalCells = gridSize * gridSize * gridSize + val imageSize = (512, 512) + val numFrames = 1000 + + logger.info(s"Grid: $gridSize³ = $totalCells cells") + logger.info(s"Image: ${imageSize._1}×${imageSize._2}") + logger.info(s"Frames: $numFrames") + + // Build complete simulation pipeline + logger.info("Building complete simulation pipeline...") + val simPipeline = buildPipeline(imageSize, 64) + + // Initialize parameters with stronger buoyancy + val params = FluidParams( + dt = 0.05f, // Time step + viscosity = 0.001f, // Low viscosity (smoke is not very viscous) + diffusion = 0.00001f, // Slight diffusion + buoyancy = 0.001f, // Strong buoyancy (hot smoke rises!) + ambient = 0.005f, // Ambient temperature + gridSize = gridSize, + windX = 0f, // Wind in X direction + windY = 0.0f, + windZ = 0f, // Wind in Z direction + ) + val paramsBuffer = createParamsBuffer(params) + + // Camera setup + // Grid is at Y=0 (bottom) to Y=gridSize (top), so look at middle height + val cameraHeight = gridSize * 0f // Camera slightly below center + val lookAtCenter = (gridSize / 2.0f, gridSize / 2.0f, gridSize / 2.0f) // Look at grid center + + // Initialize state buffers + logger.info("Initializing fluid state...") + val velocityCurrent = createZeroVec4Buffer(totalCells) + val velocityPrevious = createZeroVec4Buffer(totalCells) + val densityCurrent = createZeroFloatBuffer(totalCells) + val densityPrevious = createZeroFloatBuffer(totalCells) + val temperatureCurrent = createZeroFloatBuffer(totalCells) + val temperaturePrevious = createZeroFloatBuffer(totalCells) + val dyeCurrent = createZeroFloatBuffer(totalCells) + val dyePrevious = createZeroFloatBuffer(totalCells) + val pressureCurrent = createZeroFloatBuffer(totalCells) + val pressurePrevious = createZeroFloatBuffer(totalCells) + val divergence = createZeroFloatBuffer(totalCells) + val renderParamsStride = totalStride(summon[GStructSchema[RenderParams]]) + val renderParamsBuffer = BufferUtils.createByteBuffer(renderParamsStride) + val cameraStride = totalStride(summon[GStructSchema[Camera3D]]) + val cameraBuffer = BufferUtils.createByteBuffer(cameraStride) + + logger.info("Creating obstacles...") + val obstacles = FieldUtils.createEmpty(gridSize) + + // Set uniform density everywhere + FieldUtils.addBox( + densityCurrent, + gridSize, + minX = 0, + maxX = gridSize - 1, + minY = 0, + maxY = gridSize - 1, + minZ = 0, + maxZ = gridSize - 1, + value = 0.5f, + ) + + // Uniform temperature (optional, for visualization) + FieldUtils.addBox( + temperatureCurrent, + gridSize, + minX = 0, + maxX = gridSize - 1, + minY = 0, + maxY = gridSize - 1, + minZ = 0, + maxZ = gridSize - 1, + value = 0.5f, + ) + + // Add dye discs at the velocity current source locations + // Discs are perpendicular to flow (X direction), circular in YZ plane + val center = gridSize / 2.0f + val currentRadius = gridSize * 0.15f + val separation = gridSize * 0.35f + val discThickness = gridSize * 0.05f // Thin disc in X direction + + // Create the spiral obstacle (Scala logo with constant radius and ribbon shape!) + FieldUtils.addSpiralObstacle( + obstacles, + gridSize, + centerX = center, + centerY = gridSize * 0.4f, + centerZ = center, + spiralRadius = gridSize * 0.1f, + spiralHeight = gridSize * 0.3f, + numTurns = 2.5f, + ribbonWidth = gridSize * 0.08f, // Width along curve (tangent) + ribbonThickness = gridSize * 0.03f, // Thickness perpendicular to curve (thin!) + ribbonHeight = gridSize * 0.07f, // Vertical height of ribbon + rotationDegrees = 180f, // Can adjust to rotate the spiral + value = 1.0f, + ) + + val region = (0 until numFrames).foldLeft( + GBufferRegion + .allocate[SimulationLayout], + ): (regionAcc, frameIdx) => + regionAcc.map: layout => + + logger.info(s"Frame $frameIdx / $numFrames") + + layout.velocityPrevious.read(velocityPrevious) + layout.dyePrevious.read(dyePrevious) + + updateScene(velocityPrevious, dyePrevious, gridSize, frameIdx) + + // Prepare output buffer for reading back + val outputBuffer = BufferUtils.createFloatBuffer(imageSize._1 * imageSize._2 * 4) + val outputBB = org.lwjgl.system.MemoryUtil.memByteBuffer(outputBuffer) + + val angle = 90 + val angleRad = angle * Math.PI.toFloat / 180.0f + val radius = gridSize * 1.4f + + // Prepare camera buffer + val camera = Camera3D.orbit( + centerX = lookAtCenter._1, + centerY = lookAtCenter._2, + centerZ = lookAtCenter._3, + radius = radius, + angle = angleRad, + height = cameraHeight, + aspectRatio = imageSize._1.toFloat / imageSize._2.toFloat, + ) + + summon[GCodec[Camera3D, Camera3D]].toByteBuffer(cameraBuffer, Array(camera)) + + // Prepare params buffer + val renderParams = RenderParams(gridSize = gridSize) + summon[GCodec[RenderParams, RenderParams]].toByteBuffer(renderParamsBuffer, Array(renderParams)) + + // Write back prepared data to PREVIOUS buffers (simulation reads from Previous) + layout.velocityPrevious.write(velocityPrevious) + layout.dyePrevious.write(dyePrevious) + // NOTE: write() with ByteBuffer does CPU->GPU transfer + // write() with case class is a shader op (GIO) - wrong! + layout.renderParams.write(renderParamsBuffer) + layout.camera.write(cameraBuffer) + + // Run complete simulation pipeline + logger.debug("Running simulation pipeline...") + simPipeline.execute(totalCells, layout) + + // Read GPU-rendered image back to CPU + layout.imageOutput.read(outputBB) + + velocityPrevious.rewind() + dyePrevious.rewind() + + // Rewind the output buffer before reading + outputBuffer.rewind() + + val outputPixels = ByteBuffer.allocateDirect(imageSize._1 * imageSize._2 * 4) + while outputBuffer.hasRemaining do + val pixel = (Math.clamp(outputBuffer.get(), 0.0f, 1.0f) * 255).toByte + outputPixels.put(pixel) + + saveFrame(outputPixels, (imageSize._1, imageSize._2), s"smoke/full_fluid_$frameIdx.png") + + logger.debug(s"Saved full_fluid_$frameIdx.png") + + // CRITICAL: Swap buffers so Current becomes Previous for next frame + // Without this, results don't propagate between frames! + layout.swap + + val resultLayout = region.runUnsafe( + init = SimulationLayout( + velocityCurrent = GBuffer(velocityCurrent), + velocityPrevious = GBuffer(velocityPrevious), + densityCurrent = GBuffer(densityCurrent), + densityPrevious = GBuffer(densityPrevious), + temperatureCurrent = GBuffer(temperatureCurrent), + temperaturePrevious = GBuffer(temperaturePrevious), + dyeCurrent = GBuffer(dyeCurrent), + dyePrevious = GBuffer(dyePrevious), + pressureCurrent = GBuffer(pressureCurrent), + pressurePrevious = GBuffer(pressurePrevious), + divergence = GBuffer(divergence), + obstacles = GBuffer(obstacles), + fluidParams = GUniform(paramsBuffer), + renderParams = GUniform(renderParamsBuffer), + camera = GUniform(cameraBuffer), + imageOutput = GBuffer[Vec4[Float32]](imageSize._1 * imageSize._2), + ), + onDone = layout => + logger.info(s"Done! Created $numFrames frames") + logger.info("Generate video with: ffmpeg -framerate 10 -i smoke/full_fluid_%d.png -c:v libx264 -pix_fmt yuv420p full_fluid.mp4"), + ) + + finally runtime.close() + + /** Copy buffer contents */ + def copyBuffer(src: ByteBuffer, dst: ByteBuffer): Unit = + src.rewind() + dst.rewind() + dst.put(src) + src.rewind() + dst.rewind() + + /** Create FluidParams buffer */ + def createParamsBuffer(params: FluidParams): ByteBuffer = + import io.computenode.cyfra.spirv.compilers.SpirvProgramCompiler.totalStride + import io.computenode.cyfra.dsl.struct.GStruct.given + import io.computenode.cyfra.core.GCodec + + val schema = summon[io.computenode.cyfra.dsl.struct.GStructSchema[FluidParams]] + val size = totalStride(schema) + val buffer = ByteBuffer.allocateDirect(size).order(ByteOrder.nativeOrder()) + + summon[GCodec[FluidParams, FluidParams]].toByteBuffer(buffer, Array(params)) + buffer.rewind() + buffer + + /** Create zero Vec4 buffer */ + def createZeroVec4Buffer(totalCells: Int): ByteBuffer = + ByteBuffer.allocateDirect(totalCells * 16).order(ByteOrder.nativeOrder()) + + /** Create zero Float32 buffer */ + def createZeroFloatBuffer(totalCells: Int): ByteBuffer = + ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder()) + + /** Save frame as PNG (flip Y: image Y=0 is top, but 3D Y=0 is bottom) */ + def saveFrame(pixels: ByteBuffer, imageSize: (Int, Int), filename: String): Unit = + val (width, height) = imageSize + val image = BufferedImage(width, height, BufferedImage.TYPE_INT_RGB) + + pixels.rewind() + for y <- 0 until height; x <- 0 until width do + val r = pixels.get() & 0xff + val g = pixels.get() & 0xff + val b = pixels.get() & 0xff + val a = pixels.get() & 0xff + + val rgb = (r << 16) | (g << 8) | b + // Flip Y coordinate: image Y=0 is top, but 3D Y=0 should be at bottom of image + image.setRGB(x, height - 1 - y, rgb) + + val file = Paths.get(filename).toFile + Option(file.getParentFile).foreach(_.mkdirs()) + ImageIO.write(image, "png", file) + + /** Add dsc-shaped velocity vector. + * + * This should be called EVERY FRAME to continuously inject velocity. Creates two disc-shaped regions with strong velocities flowing toward each + * other. + * + * @param velocityBuffer + * Velocity field to modify + * @param dyeBuffer + * Dye field to modify + * @param gridSize + * Grid resolution + * @param frameIdx + * Current frame index + */ + def updateScene(velocityBuffer: ByteBuffer, dyeBuffer: ByteBuffer, gridSize: Int, frameIdx: Int): Unit = + val center = gridSize / 2.0f + val currentRadius = gridSize * 0.15f + val separation = gridSize * 0.35f + val discThickness = gridSize * 0.05f + val collisionSpeed = 2.0f + + val leftDiscX = center - separation + + FieldUtils.addDiscVecPerpToX( + velocityBuffer, + gridSize, + centerX = leftDiscX, + centerY = center, + centerZ = center, + radius = currentRadius * 3f, + thickness = discThickness * 100f, + velocityX = collisionSpeed, + velocityY = 0.0f, + velocityZ = 0.0f, + ) + + if frameIdx < 20 then + FieldUtils.addDiscPerpToX( + dyeBuffer, + gridSize, + centerX = leftDiscX, + centerY = center, + centerZ = center, + radius = currentRadius, + thickness = discThickness, + value = 0.5f, + ) diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/FluidParameters.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/FluidParameters.scala new file mode 100644 index 00000000..35d8a2c5 --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/FluidParameters.scala @@ -0,0 +1,59 @@ +package io.computenode.cyfra.fluids.solver + +import io.computenode.cyfra.dsl.{*, given} + +/** Simulation parameters for 3D fluid dynamics. + * + * @param dt + * Time step size (seconds) + * @param viscosity + * Kinematic viscosity (momentum diffusion coefficient) + * @param diffusion + * Density diffusion coefficient + * @param buoyancy + * Buoyancy force strength (how much hot fluid rises) + * @param ambient + * Ambient temperature reference + * @param gridSize + * Grid resolution (gridSize³ voxels) + */ +case class FluidParams( + dt: Float32, + viscosity: Float32, + diffusion: Float32, + buoyancy: Float32, + ambient: Float32, + gridSize: Int32, + windX: Float32, + windY: Float32, + windZ: Float32, +) extends GStruct[FluidParams] + +object FluidParams: + /** Default parameters for smoke simulation */ + def smoke(gridSize: Int): FluidParams = + FluidParams( + dt = 0.1f, + viscosity = 0.00001f, + diffusion = 0.001f, + buoyancy = 0.5f, + ambient = 0.0f, + gridSize = gridSize, + windX = 0.0f, + windY = 0.0f, + windZ = 0.0f, + ) + + /** Parameters for thick, viscous fluid */ + def thickFluid(gridSize: Int): FluidParams = + FluidParams( + dt = 0.05f, + viscosity = 0.01f, + diffusion = 0.0001f, + buoyancy = 0.0f, + ambient = 0.0f, + gridSize = gridSize, + windX = 0.0f, + windY = 0.0f, + windZ = 0.0f, + ) diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/FluidState.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/FluidState.scala new file mode 100644 index 00000000..0b32ae6a --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/FluidState.scala @@ -0,0 +1,43 @@ +package io.computenode.cyfra.fluids.solver + +import io.computenode.cyfra.core.layout.Layout +import io.computenode.cyfra.dsl.{*, given} + +/** GPU fluid state buffers (single-buffered) Note: Using Vec4 for velocity to ensure proper 16-byte alignment (std430) + */ +case class FluidState( + velocity: GBuffer[Vec4[Float32]], // 3D velocity field (w=0) + pressure: GBuffer[Float32], // Pressure field + density: GBuffer[Float32], // Density/smoke field + temperature: GBuffer[Float32], // Temperature field + dye: GBuffer[Float32], // Dye/tracer field (passive advection) + divergence: GBuffer[Float32], // Divergence scratch buffer + obstacles: GBuffer[Float32], // Obstacle field (<=0=fluid, >0=solid with color) + params: GUniform[FluidParams], // Simulation parameters +) derives Layout + +/** Double-buffered state for read-while-write operations. Layouts cannot be nested, so we flatten all buffers to top level. + */ +case class FluidStateDouble( + // Current state buffers + velocityCurrent: GBuffer[Vec4[Float32]], + pressureCurrent: GBuffer[Float32], + densityCurrent: GBuffer[Float32], + temperatureCurrent: GBuffer[Float32], + dyeCurrent: GBuffer[Float32], + divergenceCurrent: GBuffer[Float32], + + // Previous state buffers (for ping-pong) + velocityPrevious: GBuffer[Vec4[Float32]], + pressurePrevious: GBuffer[Float32], + densityPrevious: GBuffer[Float32], + temperaturePrevious: GBuffer[Float32], + dyePrevious: GBuffer[Float32], + divergencePrevious: GBuffer[Float32], + + // Shared read-only buffers + obstacles: GBuffer[Float32], // Obstacle field (<=0=fluid, >0=solid with color) + + // Shared parameters + params: GUniform[FluidParams], +) derives Layout diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/AdvectionProgram.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/AdvectionProgram.scala new file mode 100644 index 00000000..9783b298 --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/AdvectionProgram.scala @@ -0,0 +1,64 @@ +package io.computenode.cyfra.fluids.solver.programs + +import io.computenode.cyfra.core.GProgram +import io.computenode.cyfra.core.GProgram.StaticDispatch +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.fluids.solver.* +import io.computenode.cyfra.fluids.solver.utils.GridUtils.* + +object AdvectionProgram: + + def create: GProgram[Int, FluidStateDouble] = + GProgram[Int, FluidStateDouble]( + layout = totalCells => + FluidStateDouble( + velocityCurrent = GBuffer[Vec4[Float32]](totalCells), + pressureCurrent = GBuffer[Float32](totalCells), + densityCurrent = GBuffer[Float32](totalCells), + temperatureCurrent = GBuffer[Float32](totalCells), + divergenceCurrent = GBuffer[Float32](totalCells), + velocityPrevious = GBuffer[Vec4[Float32]](totalCells), + pressurePrevious = GBuffer[Float32](totalCells), + densityPrevious = GBuffer[Float32](totalCells), + temperaturePrevious = GBuffer[Float32](totalCells), + divergencePrevious = GBuffer[Float32](totalCells), + obstacles = GBuffer[Float32](totalCells), + dyeCurrent = GBuffer[Float32](totalCells), + dyePrevious = GBuffer[Float32](totalCells), + params = GUniform[FluidParams](), + ), + dispatch = (_, totalCells) => { + val workgroupSize = 256 + val numWorkgroups = (totalCells + workgroupSize - 1) / workgroupSize + StaticDispatch((numWorkgroups, 1, 1)) + }, + workgroupSize = (256, 1, 1), + ): state => + val idx = GIO.invocationId + val params = state.params.read + val n = params.gridSize + val totalCells = n * n * n + + GIO.when(idx < totalCells): + val (x, y, z) = idxTo3D(idx, n) + val pos = vec3(x.asFloat, y.asFloat, z.asFloat) + + val vel = GIO.read(state.velocityPrevious, idx) + + val vel3 = vec3(vel.x, vel.y, vel.z) + val prevPos = pos - vel3 * params.dt + + val interpolatedVel = trilinearInterpolateVec4(state.velocityPrevious, prevPos, n) + + val interpolatedDensity = trilinearInterpolateFloat32(state.densityPrevious, prevPos, n) + + val interpolatedTemperature = trilinearInterpolateFloat32(state.temperaturePrevious, prevPos, n) + + val interpolatedDye = trilinearInterpolateFloat32(state.dyePrevious, prevPos, n) + + for + _ <- GIO.write(state.velocityCurrent, idx, interpolatedVel) + _ <- GIO.write(state.densityCurrent, idx, interpolatedDensity) + _ <- GIO.write(state.temperatureCurrent, idx, interpolatedTemperature) + _ <- GIO.write(state.dyeCurrent, idx, interpolatedDye) + yield GStruct.Empty() diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/BoundaryProgram.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/BoundaryProgram.scala new file mode 100644 index 00000000..92856a0c --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/BoundaryProgram.scala @@ -0,0 +1,53 @@ +package io.computenode.cyfra.fluids.solver.programs + +import io.computenode.cyfra.core.GProgram +import io.computenode.cyfra.core.GProgram.StaticDispatch +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.fluids.solver.* +import io.computenode.cyfra.fluids.solver.utils.{GridUtils, ObstacleUtils} +import GridUtils.idxTo3D + +/** Applies no-slip boundary conditions at domain walls and obstacles */ +object BoundaryProgram: + + def create: GProgram[Int, FluidState] = + GProgram[Int, FluidState]( + layout = totalCells => + FluidState( + velocity = GBuffer[Vec4[Float32]](totalCells), + pressure = GBuffer[Float32](totalCells), + density = GBuffer[Float32](totalCells), + temperature = GBuffer[Float32](totalCells), + divergence = GBuffer[Float32](totalCells), + obstacles = GBuffer[Float32](totalCells), + dye = GBuffer[Float32](totalCells), + params = GUniform[FluidParams](), + ), + dispatch = (_, totalCells) => { + val workgroupSize = 256 + val numWorkgroups = (totalCells + workgroupSize - 1) / workgroupSize + StaticDispatch((numWorkgroups, 1, 1)) + }, + workgroupSize = (256, 1, 1), + ): state => + val idx = GIO.invocationId + val params = state.params.read + val n = params.gridSize + val totalCells = n * n * n + + GIO.when(idx < totalCells): + val (x, y, z) = idxTo3D(idx, n) + + val onDomainBoundary = + (x === 0) || + (x === n - 1) || + (y === 0) || + (y === n - 1) || + (z === 0) || + (z === n - 1) + + val isSolid = ObstacleUtils.isSolid(state.obstacles, idx, totalCells) + + GIO.when(onDomainBoundary || isSolid): + val boundaryVel = vec4(0.0f, 0.0f, 0.0f, 0.0f) + GIO.write(state.velocity, idx, boundaryVel) diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/DiffusionProgram.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/DiffusionProgram.scala new file mode 100644 index 00000000..f8a444af --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/DiffusionProgram.scala @@ -0,0 +1,63 @@ +package io.computenode.cyfra.fluids.solver.programs + +import io.computenode.cyfra.core.GProgram +import io.computenode.cyfra.core.GProgram.StaticDispatch +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.fluids.solver.* +import io.computenode.cyfra.fluids.solver.utils.GridUtils.* + +/** Implements diffusion via Jacobi iteration. Solves: (I - ν·Δt·∇²)v_new = v_old + */ +object DiffusionProgram: + + def create: GProgram[Int, FluidStateDouble] = + GProgram[Int, FluidStateDouble]( + layout = totalCells => + FluidStateDouble( + velocityCurrent = GBuffer[Vec4[Float32]](totalCells), + pressureCurrent = GBuffer[Float32](totalCells), + densityCurrent = GBuffer[Float32](totalCells), + temperatureCurrent = GBuffer[Float32](totalCells), + divergenceCurrent = GBuffer[Float32](totalCells), + velocityPrevious = GBuffer[Vec4[Float32]](totalCells), + pressurePrevious = GBuffer[Float32](totalCells), + densityPrevious = GBuffer[Float32](totalCells), + temperaturePrevious = GBuffer[Float32](totalCells), + divergencePrevious = GBuffer[Float32](totalCells), + obstacles = GBuffer[Float32](totalCells), + dyeCurrent = GBuffer[Float32](totalCells), + dyePrevious = GBuffer[Float32](totalCells), + params = GUniform[FluidParams](), + ), + dispatch = (_, totalCells) => { + val workgroupSize = 256 + val numWorkgroups = (totalCells + workgroupSize - 1) / workgroupSize + StaticDispatch((numWorkgroups, 1, 1)) + }, + workgroupSize = (256, 1, 1), + ): state => + val idx = GIO.invocationId + val params = state.params.read + val n = params.gridSize + val totalCells = n * n * n + + GIO.when(idx < totalCells): + val (x, y, z) = idxTo3D(idx, n) + + val alpha = 1.0f / (params.viscosity * params.dt) + val beta = 1.0f / (6.0f + alpha) + + val center = GIO.read(state.velocityPrevious, idx) + + val xm = readVec4Safe(state.velocityPrevious, x - 1, y, z, n) + val xp = readVec4Safe(state.velocityPrevious, x + 1, y, z, n) + val ym = readVec4Safe(state.velocityPrevious, x, y - 1, z, n) + val yp = readVec4Safe(state.velocityPrevious, x, y + 1, z, n) + val zm = readVec4Safe(state.velocityPrevious, x, y, z - 1, n) + val zp = readVec4Safe(state.velocityPrevious, x, y, z + 1, n) + + val neighborSum = xm + xp + ym + yp + zm + zp + + val newVel = (center * alpha + neighborSum) * beta + + GIO.write(state.velocityCurrent, idx, newVel) diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/DissipativeBoundaryProgram.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/DissipativeBoundaryProgram.scala new file mode 100644 index 00000000..8150fc42 --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/DissipativeBoundaryProgram.scala @@ -0,0 +1,112 @@ +package io.computenode.cyfra.fluids.solver.programs + +import io.computenode.cyfra.core.GProgram +import io.computenode.cyfra.core.GProgram.StaticDispatch +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.fluids.solver.* +import io.computenode.cyfra.fluids.solver.utils.{GridUtils, ObstacleUtils} +import GridUtils.idxTo3D + +/** Free-slip boundary conditions with density/temperature dissipation. + * + * Velocity slides tangentially along surfaces (proper free-slip). Density and temperature gradually fade at boundaries to prevent accumulation. + */ +object DissipativeBoundaryProgram: + + def create: GProgram[Int, FluidState] = + GProgram[Int, FluidState]( + layout = totalCells => + FluidState( + velocity = GBuffer[Vec4[Float32]](totalCells), + pressure = GBuffer[Float32](totalCells), + density = GBuffer[Float32](totalCells), + temperature = GBuffer[Float32](totalCells), + divergence = GBuffer[Float32](totalCells), + obstacles = GBuffer[Float32](totalCells), + dye = GBuffer[Float32](totalCells), + params = GUniform[FluidParams](), + ), + dispatch = (_, totalCells) => { + val workgroupSize = 256 + val numWorkgroups = (totalCells + workgroupSize - 1) / workgroupSize + StaticDispatch((numWorkgroups, 1, 1)) + }, + workgroupSize = (256, 1, 1), + ): state => + val idx = GIO.invocationId + val params = state.params.read + val n = params.gridSize + val totalCells = n * n * n + + GIO.when(idx < totalCells): + val (x, y, z) = idxTo3D(idx, n) + + val onDomainBoundary = + (x === 0) || + (x === n - 1) || + (y === 0) || + (y === n - 1) || + (z === 0) || + (z === n - 1) + val isSolid = ObstacleUtils.isSolid(state.obstacles, idx, totalCells) + + val solidXP = ObstacleUtils.isSolidAt(state.obstacles, x + 1, y, z, n) + val solidXM = ObstacleUtils.isSolidAt(state.obstacles, x - 1, y, z, n) + val solidYP = ObstacleUtils.isSolidAt(state.obstacles, x, y + 1, z, n) + val solidYM = ObstacleUtils.isSolidAt(state.obstacles, x, y - 1, z, n) + val solidZP = ObstacleUtils.isSolidAt(state.obstacles, x, y, z + 1, n) + val solidZM = ObstacleUtils.isSolidAt(state.obstacles, x, y, z - 1, n) + val adjacentToObstacle = (solidXP || solidXM || solidYP || solidYM || solidZP || solidZM) && !isSolid + + for + _ <- GIO.when(isSolid): + for + _ <- GIO.write(state.velocity, idx, vec4(0.0f, 0.0f, 0.0f, 0.0f)) + _ <- GIO.write(state.density, idx, 0.0f) + _ <- GIO.write(state.temperature, idx, 0.0f) + yield GStruct.Empty() + + _ <- GIO.when(adjacentToObstacle && !onDomainBoundary): + val vel = state.velocity.read(idx) + val vel3 = vec3(vel.x, vel.y, vel.z) + + val nx = when(solidXP)(1.0f).otherwise(0.0f) + when(solidXM)(-1.0f).otherwise(0.0f) + val ny = when(solidYP)(1.0f).otherwise(0.0f) + when(solidYM)(-1.0f).otherwise(0.0f) + val nz = when(solidZP)(1.0f).otherwise(0.0f) + when(solidZM)(-1.0f).otherwise(0.0f) + val obstacleNormal = vec3(nx, ny, nz) + + val normalLength = sqrt((obstacleNormal dot obstacleNormal) + 1e-8f) + val normalNorm = obstacleNormal * (1.0f / normalLength) + + val normalComponent = vel3 dot normalNorm + val tangentialVel = vel3 - (normalNorm * normalComponent) + val newVel = vec4(tangentialVel.x, tangentialVel.y, tangentialVel.z, 0.0f) + + GIO.write(state.velocity, idx, newVel) + + _ <- GIO.when(onDomainBoundary && !isSolid && !adjacentToObstacle): + val vel = state.velocity.read(idx) + val vel3 = vec3(vel.x, vel.y, vel.z) + + val nx = when(x === 0)(1.0f).elseWhen(x === n - 1)(-1.0f).otherwise(0.0f) + val ny = when(y === 0)(1.0f).elseWhen(y === n - 1)(-1.0f).otherwise(0.0f) + val nz = when(z === 0)(1.0f).elseWhen(z === n - 1)(-1.0f).otherwise(0.0f) + val normal = vec3(nx, ny, nz) + + val normalLength = sqrt((normal dot normal) + 1e-8f) + val normalNorm = normal * (1.0f / normalLength) + + val normalComponent = vel3 dot normalNorm + val tangentialVel = vel3 - (normalNorm * normalComponent) + val newVel = vec4(tangentialVel.x, tangentialVel.y, tangentialVel.z, 0.0f) + + val currentDensity = state.density.read(idx) + val currentTemp = state.temperature.read(idx) + val dissipationFactor = 0.95f + + for + _ <- GIO.write(state.velocity, idx, newVel) + _ <- GIO.write(state.density, idx, currentDensity * dissipationFactor) + _ <- GIO.write(state.temperature, idx, currentTemp * dissipationFactor) + yield GStruct.Empty() + yield GStruct.Empty() diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/ForcesProgram.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/ForcesProgram.scala new file mode 100644 index 00000000..5c766170 --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/ForcesProgram.scala @@ -0,0 +1,41 @@ +package io.computenode.cyfra.fluids.solver.programs + +import io.computenode.cyfra.core.GProgram +import io.computenode.cyfra.core.GProgram.StaticDispatch +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.fluids.solver.* + +object ForcesProgram: + + def create: GProgram[Int, FluidState] = + GProgram[Int, FluidState]( + layout = totalCells => + FluidState( + velocity = GBuffer[Vec4[Float32]](totalCells), + pressure = GBuffer[Float32](totalCells), + density = GBuffer[Float32](totalCells), + temperature = GBuffer[Float32](totalCells), + divergence = GBuffer[Float32](totalCells), + obstacles = GBuffer[Float32](totalCells), + dye = GBuffer[Float32](totalCells), + params = GUniform[FluidParams](), + ), + dispatch = (_, totalCells) => { + val workgroupSize = 256 + val numWorkgroups = (totalCells + workgroupSize - 1) / workgroupSize + StaticDispatch((numWorkgroups, 1, 1)) + }, + workgroupSize = (256, 1, 1), + ): state => + val idx = GIO.invocationId + val params = state.params.read + val totalCells = params.gridSize * params.gridSize * params.gridSize + + GIO.when(idx < totalCells): + val oldVel = GIO.read(state.velocity, idx) + val temp = GIO.read(state.temperature, idx) + + val forces = vec4(params.windX, params.buoyancy * (temp - params.ambient) + params.windY, params.windZ, 0.0f) + val newVel = oldVel + forces * params.dt + + GIO.write(state.velocity, idx, newVel) diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/FreeSlipBoundaryProgram.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/FreeSlipBoundaryProgram.scala new file mode 100644 index 00000000..84591c26 --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/FreeSlipBoundaryProgram.scala @@ -0,0 +1,104 @@ +package io.computenode.cyfra.fluids.solver.programs + +import io.computenode.cyfra.core.GProgram +import io.computenode.cyfra.core.GProgram.StaticDispatch +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.fluids.solver.* +import io.computenode.cyfra.fluids.solver.utils.{GridUtils, ObstacleUtils} +import GridUtils.idxTo3D + +/** Proper free-slip boundary conditions - fluid slides tangentially along surfaces. + * + * Removes only the normal component of velocity, preserving tangential flow. This allows fluid to slide freely along walls and obstacles. + */ +object FreeSlipBoundaryProgram: + + def create: GProgram[Int, FluidState] = + GProgram[Int, FluidState]( + layout = totalCells => + FluidState( + velocity = GBuffer[Vec4[Float32]](totalCells), + pressure = GBuffer[Float32](totalCells), + density = GBuffer[Float32](totalCells), + temperature = GBuffer[Float32](totalCells), + divergence = GBuffer[Float32](totalCells), + obstacles = GBuffer[Float32](totalCells), + dye = GBuffer[Float32](totalCells), + params = GUniform[FluidParams](), + ), + dispatch = (_, totalCells) => { + val workgroupSize = 256 + val numWorkgroups = (totalCells + workgroupSize - 1) / workgroupSize + StaticDispatch((numWorkgroups, 1, 1)) + }, + workgroupSize = (256, 1, 1), + ): state => + val idx = GIO.invocationId + val params = state.params.read + val n = params.gridSize + val totalCells = n * n * n + + GIO.when(idx < totalCells): + val (x, y, z) = idxTo3D(idx, n) + + val onDomainBoundary = + (x === 0) || + (x === n - 1) || + (y === 0) || + (y === n - 1) || + (z === 0) || + (z === n - 1) + val isSolid = ObstacleUtils.isSolid(state.obstacles, idx, totalCells) + + val solidXP = ObstacleUtils.isSolidAt(state.obstacles, x + 1, y, z, n) + val solidXM = ObstacleUtils.isSolidAt(state.obstacles, x - 1, y, z, n) + val solidYP = ObstacleUtils.isSolidAt(state.obstacles, x, y + 1, z, n) + val solidYM = ObstacleUtils.isSolidAt(state.obstacles, x, y - 1, z, n) + val solidZP = ObstacleUtils.isSolidAt(state.obstacles, x, y, z + 1, n) + val solidZM = ObstacleUtils.isSolidAt(state.obstacles, x, y, z - 1, n) + val adjacentToObstacle = (solidXP || solidXM || solidYP || solidYM || solidZP || solidZM) && !isSolid + + for + _ <- GIO.when(isSolid): + for + _ <- GIO.write(state.velocity, idx, vec4(0.0f, 0.0f, 0.0f, 0.0f)) + _ <- GIO.write(state.density, idx, 0.0f) + _ <- GIO.write(state.temperature, idx, 0.0f) + yield GStruct.Empty() + + _ <- GIO.when(adjacentToObstacle && !onDomainBoundary): + val vel = state.velocity.read(idx) + val vel3 = vec3(vel.x, vel.y, vel.z) + + val nx = when(solidXP)(1.0f).otherwise(0.0f) + when(solidXM)(-1.0f).otherwise(0.0f) + val ny = when(solidYP)(1.0f).otherwise(0.0f) + when(solidYM)(-1.0f).otherwise(0.0f) + val nz = when(solidZP)(1.0f).otherwise(0.0f) + when(solidZM)(-1.0f).otherwise(0.0f) + val obstacleNormal = vec3(nx, ny, nz) + + val normalLength = sqrt((obstacleNormal dot obstacleNormal) + 1e-8f) + val normalNorm = obstacleNormal * (1.0f / normalLength) + + val normalComponent = vel3 dot normalNorm + val tangentialVel = vel3 - (normalNorm * normalComponent) + + val newVel = vec4(tangentialVel.x, tangentialVel.y, tangentialVel.z, 0.0f) + GIO.write(state.velocity, idx, newVel) + + _ <- GIO.when(onDomainBoundary && !isSolid && !adjacentToObstacle): + val vel = state.velocity.read(idx) + val vel3 = vec3(vel.x, vel.y, vel.z) + + val nx = when(x === 0)(1.0f).elseWhen(x === n - 1)(-1.0f).otherwise(0.0f) + val ny = when(y === 0)(1.0f).elseWhen(y === n - 1)(-1.0f).otherwise(0.0f) + val nz = when(z === 0)(1.0f).elseWhen(z === n - 1)(-1.0f).otherwise(0.0f) + val normal = vec3(nx, ny, nz) + + val normalLength = sqrt((normal dot normal) + 1e-8f) + val normalNorm = normal * (1.0f / normalLength) + + val normalComponent = vel3 dot normalNorm + val tangentialVel = vel3 - (normalNorm * normalComponent) + + val newVel = vec4(tangentialVel.x, tangentialVel.y, tangentialVel.z, 0.0f) + GIO.write(state.velocity, idx, newVel) + yield GStruct.Empty() diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/NeumannBoundaryProgram.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/NeumannBoundaryProgram.scala new file mode 100644 index 00000000..3094a631 --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/NeumannBoundaryProgram.scala @@ -0,0 +1,72 @@ +package io.computenode.cyfra.fluids.solver.programs + +import io.computenode.cyfra.core.GProgram +import io.computenode.cyfra.core.GProgram.StaticDispatch +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.fluids.solver.* +import io.computenode.cyfra.fluids.solver.utils.{GridUtils, ObstacleUtils} +import GridUtils.{idxTo3D, coord3dToIdx} + +/** Pure Neumann boundary conditions matching GPU Gems Chapter 38. + * + * Implements ∂u/∂n = 0 at boundaries (zero gradient normal to boundary). In practice: boundary cells copy values from their interior neighbors. + * + * This is simpler than free-slip or outflow - just ensures smooth flow at edges. + */ +object NeumannBoundaryProgram: + + def create: GProgram[Int, FluidState] = + GProgram[Int, FluidState]( + layout = totalCells => + FluidState( + velocity = GBuffer[Vec4[Float32]](totalCells), + pressure = GBuffer[Float32](totalCells), + density = GBuffer[Float32](totalCells), + temperature = GBuffer[Float32](totalCells), + divergence = GBuffer[Float32](totalCells), + obstacles = GBuffer[Float32](totalCells), + dye = GBuffer[Float32](totalCells), + params = GUniform[FluidParams](), + ), + dispatch = (_, totalCells) => { + val workgroupSize = 256 + val numWorkgroups = (totalCells + workgroupSize - 1) / workgroupSize + StaticDispatch((numWorkgroups, 1, 1)) + }, + workgroupSize = (256, 1, 1), + ): state => + val idx = GIO.invocationId + val params = state.params.read + val n = params.gridSize + val totalCells = n * n * n + + GIO.when(idx < totalCells): + val (x, y, z) = idxTo3D(idx, n) + + val onBoundary = + (x === 0) || + (x === n - 1) || + (y === 0) || + (y === n - 1) || + (z === 0) || + (z === n - 1) || + (ObstacleUtils.isSolid(state.obstacles, idx, totalCells)) + + GIO.when(onBoundary): + val xInterior = when(x === 0)(1: Int32).elseWhen(x === n - 1)(n - 2).otherwise(x) + val yInterior = when(y === 0)(1: Int32).elseWhen(y === n - 1)(n - 2).otherwise(y) + val zInterior = when(z === 0)(1: Int32).elseWhen(z === n - 1)(n - 2).otherwise(z) + + val interiorIdx = coord3dToIdx(xInterior, yInterior, zInterior, n) + + val interiorVel = state.velocity.read(interiorIdx) + val interiorDensity = state.density.read(interiorIdx) + val interiorTemp = state.temperature.read(interiorIdx) + val interiorPressure = state.pressure.read(interiorIdx) + + for + _ <- GIO.write(state.velocity, idx, interiorVel) + _ <- GIO.write(state.density, idx, interiorDensity) + _ <- GIO.write(state.temperature, idx, interiorTemp) + _ <- GIO.write(state.pressure, idx, interiorPressure) + yield GStruct.Empty() diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/OutflowBoundaryProgram.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/OutflowBoundaryProgram.scala new file mode 100644 index 00000000..49c4b17a --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/OutflowBoundaryProgram.scala @@ -0,0 +1,120 @@ +package io.computenode.cyfra.fluids.solver.programs + +import io.computenode.cyfra.core.GProgram +import io.computenode.cyfra.core.GProgram.StaticDispatch +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.fluids.solver.* +import io.computenode.cyfra.fluids.solver.utils.{GridUtils, ObstacleUtils} +import GridUtils.{idxTo3D, coord3dToIdx} + +/** Boundary conditions with outflow at top and proper free-slip at other boundaries. + * + * - Top: Smoke escapes freely (outflow condition) + * - Sides/Bottom: Proper free-slip (tangential flow preserved) + * - Obstacles: Free-slip (fluid slides around) + */ +object OutflowBoundaryProgram: + + def create: GProgram[Int, FluidState] = + GProgram[Int, FluidState]( + layout = totalCells => + FluidState( + velocity = GBuffer[Vec4[Float32]](totalCells), + pressure = GBuffer[Float32](totalCells), + density = GBuffer[Float32](totalCells), + temperature = GBuffer[Float32](totalCells), + divergence = GBuffer[Float32](totalCells), + obstacles = GBuffer[Float32](totalCells), + dye = GBuffer[Float32](totalCells), + params = GUniform[FluidParams](), + ), + dispatch = (_, totalCells) => { + val workgroupSize = 256 + val numWorkgroups = (totalCells + workgroupSize - 1) / workgroupSize + StaticDispatch((numWorkgroups, 1, 1)) + }, + workgroupSize = (256, 1, 1), + ): state => + val idx = GIO.invocationId + val params = state.params.read + val n = params.gridSize + val totalCells = n * n * n + + GIO.when(idx < totalCells): + val (x, y, z) = idxTo3D(idx, n) + + val isTop = y === (n - 1) + val isSolid = ObstacleUtils.isSolid(state.obstacles, idx, totalCells) + val onDomainBoundary = + (x === 0) || + (x === n - 1) || + (y === 0) || + (z === 0) || + (z === n - 1) + val onOtherBoundary = onDomainBoundary && !isTop + + val solidXP = ObstacleUtils.isSolidAt(state.obstacles, x + 1, y, z, n) + val solidXM = ObstacleUtils.isSolidAt(state.obstacles, x - 1, y, z, n) + val solidYP = ObstacleUtils.isSolidAt(state.obstacles, x, y + 1, z, n) + val solidYM = ObstacleUtils.isSolidAt(state.obstacles, x, y - 1, z, n) + val solidZP = ObstacleUtils.isSolidAt(state.obstacles, x, y, z + 1, n) + val solidZM = ObstacleUtils.isSolidAt(state.obstacles, x, y, z - 1, n) + val adjacentToObstacle = (solidXP || solidXM || solidYP || solidYM || solidZP || solidZM) && !isSolid + + for + _ <- GIO.when(isTop && !isSolid): + val belowIdx = coord3dToIdx(x, y - 1, z, n) + val belowVel = state.velocity.read(belowIdx) + val belowDensity = state.density.read(belowIdx) + val belowTemp = state.temperature.read(belowIdx) + + val outflowVel = vec4(belowVel.x * 0.95f, belowVel.y, belowVel.z * 0.95f, 0.0f) + for + _ <- GIO.write(state.velocity, idx, outflowVel) + _ <- GIO.write(state.density, idx, belowDensity * 0.9f) + _ <- GIO.write(state.temperature, idx, belowTemp * 0.9f) + yield GStruct.Empty() + + _ <- GIO.when(isSolid): + for + _ <- GIO.write(state.velocity, idx, vec4(0.0f, 0.0f, 0.0f, 0.0f)) + _ <- GIO.write(state.density, idx, 0.0f) + _ <- GIO.write(state.temperature, idx, 0.0f) + yield GStruct.Empty() + + _ <- GIO.when(adjacentToObstacle && !onDomainBoundary): + val vel = state.velocity.read(idx) + val vel3 = vec3(vel.x, vel.y, vel.z) + + val nx = when(solidXP)(1.0f).otherwise(0.0f) + when(solidXM)(-1.0f).otherwise(0.0f) + val ny = when(solidYP)(1.0f).otherwise(0.0f) + when(solidYM)(-1.0f).otherwise(0.0f) + val nz = when(solidZP)(1.0f).otherwise(0.0f) + when(solidZM)(-1.0f).otherwise(0.0f) + val obstacleNormal = vec3(nx, ny, nz) + + val normalLength = sqrt((obstacleNormal dot obstacleNormal) + 1e-8f) + val normalNorm = obstacleNormal * (1.0f / normalLength) + + val normalComponent = vel3 dot normalNorm + val tangentialVel = vel3 - (normalNorm * normalComponent) + val newVel = vec4(tangentialVel.x, tangentialVel.y, tangentialVel.z, 0.0f) + + GIO.write(state.velocity, idx, newVel) + + _ <- GIO.when(onOtherBoundary && !isSolid && !adjacentToObstacle): + val vel = state.velocity.read(idx) + val vel3 = vec3(vel.x, vel.y, vel.z) + + val nx = when(x === 0)(1.0f).elseWhen(x === n - 1)(-1.0f).otherwise(0.0f) + val ny = when(y === 0)(1.0f).otherwise(0.0f) + val nz = when(z === 0)(1.0f).elseWhen(z === n - 1)(-1.0f).otherwise(0.0f) + val normal = vec3(nx, ny, nz) + + val normalLength = sqrt((normal dot normal) + 1e-8f) + val normalNorm = normal * (1.0f / normalLength) + + val normalComponent = vel3 dot normalNorm + val tangentialVel = vel3 - (normalNorm * normalComponent) + val newVel = vec4(tangentialVel.x, tangentialVel.y, tangentialVel.z, 0.0f) + + GIO.write(state.velocity, idx, newVel) + yield GStruct.Empty() diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/ProjectionProgram.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/ProjectionProgram.scala new file mode 100644 index 00000000..f0119fca --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/ProjectionProgram.scala @@ -0,0 +1,185 @@ +package io.computenode.cyfra.fluids.solver.programs + +import io.computenode.cyfra.core.GProgram +import io.computenode.cyfra.core.GProgram.StaticDispatch +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.fluids.solver.* +import io.computenode.cyfra.fluids.solver.utils.{GridUtils, ObstacleUtils} +import GridUtils.* + +/** Pressure projection programs for enforcing incompressibility */ +object ProjectionProgram: + + /** Step 1: Compute divergence of velocity field */ + def divergence: GProgram[Int, FluidState] = + GProgram[Int, FluidState]( + layout = totalCells => + FluidState( + velocity = GBuffer[Vec4[Float32]](totalCells), + pressure = GBuffer[Float32](totalCells), + density = GBuffer[Float32](totalCells), + temperature = GBuffer[Float32](totalCells), + divergence = GBuffer[Float32](totalCells), + obstacles = GBuffer[Float32](totalCells), + dye = GBuffer[Float32](totalCells), + params = GUniform[FluidParams](), + ), + dispatch = (_, totalCells) => { + val workgroupSize = 256 + val numWorkgroups = (totalCells + workgroupSize - 1) / workgroupSize + StaticDispatch((numWorkgroups, 1, 1)) + }, + workgroupSize = (256, 1, 1), + ): state => + val idx = GIO.invocationId + val params = state.params.read + val n = params.gridSize + + val z = idx / (n * n) + val y = (idx / n).mod(n) + val x = idx.mod(n) + + val isSolid = ObstacleUtils.isSolid(state.obstacles, idx, n) + + GIO.when(!isSolid): + val velCenter = GIO.read(state.velocity, idx) + + val solidXP = ObstacleUtils.isSolidAt(state.obstacles, x + 1, y, z, n) + val solidXM = ObstacleUtils.isSolidAt(state.obstacles, x - 1, y, z, n) + val solidYP = ObstacleUtils.isSolidAt(state.obstacles, x, y + 1, z, n) + val solidYM = ObstacleUtils.isSolidAt(state.obstacles, x, y - 1, z, n) + val solidZP = ObstacleUtils.isSolidAt(state.obstacles, x, y, z + 1, n) + val solidZM = ObstacleUtils.isSolidAt(state.obstacles, x, y, z - 1, n) + + val velXP = readVec4Safe(state.velocity, x + 1, y, z, n) + val velXM = readVec4Safe(state.velocity, x - 1, y, z, n) + val velYP = readVec4Safe(state.velocity, x, y + 1, z, n) + val velYM = readVec4Safe(state.velocity, x, y - 1, z, n) + val velZP = readVec4Safe(state.velocity, x, y, z + 1, n) + val velZM = readVec4Safe(state.velocity, x, y, z - 1, n) + + val dx = when(solidXP && solidXM)(0.0f).elseWhen(solidXP)(-velCenter.x).elseWhen(solidXM)(velCenter.x).otherwise((velXP.x - velXM.x) * 0.5f) + + val dy = when(solidYP && solidYM)(0.0f).elseWhen(solidYP)(-velCenter.y).elseWhen(solidYM)(velCenter.y).otherwise((velYP.y - velYM.y) * 0.5f) + + val dz = when(solidZP && solidZM)(0.0f).elseWhen(solidZP)(-velCenter.z).elseWhen(solidZM)(velCenter.z).otherwise((velZP.z - velZM.z) * 0.5f) + + val div = dx + dy + dz + + GIO.write(state.divergence, idx, div) + + /** Step 2: Solve Poisson equation for pressure via Jacobi iteration */ + def pressureSolve: GProgram[Int, FluidStateDouble] = + GProgram[Int, FluidStateDouble]( + layout = totalCells => + FluidStateDouble( + velocityCurrent = GBuffer[Vec4[Float32]](totalCells), + pressureCurrent = GBuffer[Float32](totalCells), + densityCurrent = GBuffer[Float32](totalCells), + temperatureCurrent = GBuffer[Float32](totalCells), + divergenceCurrent = GBuffer[Float32](totalCells), + velocityPrevious = GBuffer[Vec4[Float32]](totalCells), + pressurePrevious = GBuffer[Float32](totalCells), + densityPrevious = GBuffer[Float32](totalCells), + temperaturePrevious = GBuffer[Float32](totalCells), + divergencePrevious = GBuffer[Float32](totalCells), + obstacles = GBuffer[Float32](totalCells), + dyeCurrent = GBuffer[Float32](totalCells), + dyePrevious = GBuffer[Float32](totalCells), + params = GUniform[FluidParams](), + ), + dispatch = (_, totalCells) => { + val workgroupSize = 256 + val numWorkgroups = (totalCells + workgroupSize - 1) / workgroupSize + StaticDispatch((numWorkgroups, 1, 1)) + }, + workgroupSize = (256, 1, 1), + ): state => + val idx = GIO.invocationId + val params = state.params.read + val n = params.gridSize + val totalCells = n * n * n + + GIO.when(idx < totalCells): + val (x, y, z) = idxTo3D(idx, n) + + val isSolid = ObstacleUtils.isSolid(state.obstacles, idx, n) + + GIO.when(!isSolid): + val div = GIO.read(state.divergenceCurrent, idx) + val pCenter = GIO.read(state.pressurePrevious, idx) + + val solidXM = ObstacleUtils.isSolidAt(state.obstacles, x - 1, y, z, n) + val solidXP = ObstacleUtils.isSolidAt(state.obstacles, x + 1, y, z, n) + val solidYM = ObstacleUtils.isSolidAt(state.obstacles, x, y - 1, z, n) + val solidYP = ObstacleUtils.isSolidAt(state.obstacles, x, y + 1, z, n) + val solidZM = ObstacleUtils.isSolidAt(state.obstacles, x, y, z - 1, n) + val solidZP = ObstacleUtils.isSolidAt(state.obstacles, x, y, z + 1, n) + + val pXM = when(solidXM)(pCenter).otherwise(readFloat32Safe(state.pressurePrevious, x - 1, y, z, n)) + val pXP = when(solidXP)(pCenter).otherwise(readFloat32Safe(state.pressurePrevious, x + 1, y, z, n)) + val pYM = when(solidYM)(pCenter).otherwise(readFloat32Safe(state.pressurePrevious, x, y - 1, z, n)) + val pYP = when(solidYP)(pCenter).otherwise(readFloat32Safe(state.pressurePrevious, x, y + 1, z, n)) + val pZM = when(solidZM)(pCenter).otherwise(readFloat32Safe(state.pressurePrevious, x, y, z - 1, n)) + val pZP = when(solidZP)(pCenter).otherwise(readFloat32Safe(state.pressurePrevious, x, y, z + 1, n)) + + val neighborSum = pXM + pXP + pYM + pYP + pZM + pZP + + val newPressure = (neighborSum - div) / 6.0f + + GIO.write(state.pressureCurrent, idx, newPressure) + + /** Step 3: Subtract pressure gradient from velocity to make it divergence-free */ + def subtractGradient: GProgram[Int, FluidState] = + GProgram[Int, FluidState]( + layout = totalCells => + FluidState( + velocity = GBuffer[Vec4[Float32]](totalCells), + pressure = GBuffer[Float32](totalCells), + density = GBuffer[Float32](totalCells), + temperature = GBuffer[Float32](totalCells), + divergence = GBuffer[Float32](totalCells), + obstacles = GBuffer[Float32](totalCells), + dye = GBuffer[Float32](totalCells), + params = GUniform[FluidParams](), + ), + dispatch = (_, totalCells) => { + val workgroupSize = 256 + val numWorkgroups = (totalCells + workgroupSize - 1) / workgroupSize + StaticDispatch((numWorkgroups, 1, 1)) + }, + workgroupSize = (256, 1, 1), + ): state => + val idx = GIO.invocationId + val params = state.params.read + val n = params.gridSize + val totalCells = n * n * n + + GIO.when(idx < totalCells): + val (x, y, z) = idxTo3D(idx, n) + + val isSolid = ObstacleUtils.isSolid(state.obstacles, idx, n) + + GIO.when(!isSolid): + val vel = GIO.read(state.velocity, idx) + val pCenter = GIO.read(state.pressure, idx) + + val solidXM = ObstacleUtils.isSolidAt(state.obstacles, x - 1, y, z, n) + val solidXP = ObstacleUtils.isSolidAt(state.obstacles, x + 1, y, z, n) + val solidYM = ObstacleUtils.isSolidAt(state.obstacles, x, y - 1, z, n) + val solidYP = ObstacleUtils.isSolidAt(state.obstacles, x, y + 1, z, n) + val solidZM = ObstacleUtils.isSolidAt(state.obstacles, x, y, z - 1, n) + val solidZP = ObstacleUtils.isSolidAt(state.obstacles, x, y, z + 1, n) + + val pXM = when(solidXM)(pCenter).otherwise(readFloat32Safe(state.pressure, x - 1, y, z, n)) + val pXP = when(solidXP)(pCenter).otherwise(readFloat32Safe(state.pressure, x + 1, y, z, n)) + val pYM = when(solidYM)(pCenter).otherwise(readFloat32Safe(state.pressure, x, y - 1, z, n)) + val pYP = when(solidYP)(pCenter).otherwise(readFloat32Safe(state.pressure, x, y + 1, z, n)) + val pZM = when(solidZM)(pCenter).otherwise(readFloat32Safe(state.pressure, x, y, z - 1, n)) + val pZP = when(solidZP)(pCenter).otherwise(readFloat32Safe(state.pressure, x, y, z + 1, n)) + + val gradPressure = vec4((pXP - pXM) * 0.5f, (pYP - pYM) * 0.5f, (pZP - pZM) * 0.5f, 0.0f) + + val newVel = vel - gradPressure + + GIO.write(state.velocity, idx, newVel) diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/SourceInjectionProgram.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/SourceInjectionProgram.scala new file mode 100644 index 00000000..2db6b382 --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/SourceInjectionProgram.scala @@ -0,0 +1,122 @@ +package io.computenode.cyfra.fluids.solver.programs + +import io.computenode.cyfra.core.GProgram +import io.computenode.cyfra.core.GProgram.StaticDispatch +import io.computenode.cyfra.core.layout.Layout +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.fluids.solver.FluidParams +import io.computenode.cyfra.fluids.solver.utils.GridUtils.* + +/** Parameters for GPU-based scene source injection. */ +case class SourceParams( + frameIdx: Int32, + discCenterX: Float32, + discCenterY: Float32, + discCenterZ: Float32, + velocityRadius: Float32, + velocityThickness: Float32, + dyeRadius: Float32, + dyeThickness: Float32, + velocityX: Float32, + velocityY: Float32, + velocityZ: Float32, + dyeValue: Float32, + dyeFrameLimit: Int32, +) extends GStruct[SourceParams] + +object SourceParams: + /** Create source parameters from grid size and frame index. */ + def default(gridSize: Int, frameIdx: Int): SourceParams = + val center = gridSize / 2.0f + val currentRadius = gridSize * 0.15f + val separation = gridSize * 0.35f + val discThickness = gridSize * 0.05f + val collisionSpeed = 2.0f + val leftDiscX = center - separation + + SourceParams( + frameIdx = frameIdx, + discCenterX = leftDiscX, + discCenterY = center, + discCenterZ = center, + velocityRadius = currentRadius * 3f, + velocityThickness = discThickness * 100f, + dyeRadius = currentRadius, + dyeThickness = discThickness, + velocityX = collisionSpeed, + velocityY = 0.0f, + velocityZ = 0.0f, + dyeValue = 0.5f, + dyeFrameLimit = 20, + ) + +/** GPU layout for source injection program. */ +case class SourceState( + velocity: GBuffer[Vec4[Float32]], + dye: GBuffer[Float32], + fluidParams: GUniform[FluidParams], + sourceParams: GUniform[SourceParams], +) derives Layout + +/** GPU program for injecting velocity and dye sources into the fluid simulation. + * + * Creates disc-shaped source regions perpendicular to the X axis: + * - Velocity is injected every frame (added to existing velocity) + * - Dye is injected only for the first N frames (added to existing dye) + */ +object SourceInjectionProgram: + + def create: GProgram[Int, SourceState] = + GProgram[Int, SourceState]( + layout = totalCells => + SourceState( + velocity = GBuffer[Vec4[Float32]](totalCells), + dye = GBuffer[Float32](totalCells), + fluidParams = GUniform[FluidParams](), + sourceParams = GUniform[SourceParams](), + ), + dispatch = (_, totalCells) => { + val workgroupSize = 256 + val numWorkgroups = (totalCells + workgroupSize - 1) / workgroupSize + StaticDispatch((numWorkgroups, 1, 1)) + }, + workgroupSize = (256, 1, 1), + ): state => + val idx = GIO.invocationId + val params = state.fluidParams.read + val source = state.sourceParams.read + val gridSize = params.gridSize + val totalCells = gridSize * gridSize * gridSize + + GIO.when(idx < totalCells): + val (x, y, z) = idxTo3D(idx, gridSize) + + // Distance from disc center in X direction + val dx = x.asFloat - source.discCenterX + val absDx = when(dx < 0.0f)(-dx).otherwise(dx) + + // Distance from disc center in YZ plane + val dy = y.asFloat - source.discCenterY + val dz = z.asFloat - source.discCenterZ + val distYZ = sqrt(dy * dy + dz * dz) + + // Check if inside velocity source disc + val insideVelDisc = (distYZ < source.velocityRadius) && (absDx < source.velocityThickness / 2.0f) + + // Compute velocity addition (0 if outside disc) + val velAddX = when(insideVelDisc)(source.velocityX).otherwise(0.0f) + val velAddY = when(insideVelDisc)(source.velocityY).otherwise(0.0f) + val velAddZ = when(insideVelDisc)(source.velocityZ).otherwise(0.0f) + + val oldVel = GIO.read(state.velocity, idx) + val newVel = vec4(oldVel.x + velAddX, oldVel.y + velAddY, oldVel.z + velAddZ, 0.0f) + GIO.write(state.velocity, idx, newVel) + + // Check if inside dye source disc (only first N frames) + val insideDyeDisc = (distYZ < source.dyeRadius) && (absDx < source.dyeThickness / 2.0f) + val shouldInjectDye = source.frameIdx < source.dyeFrameLimit + + // Compute dye addition (0 if outside disc or past frame limit) + val dyeAdd = when(shouldInjectDye && insideDyeDisc)(source.dyeValue).otherwise(0.0f) + val oldDye = GIO.read(state.dye, idx) + GIO.write(state.dye, idx, oldDye + dyeAdd) diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/VorticityConfinementProgram.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/VorticityConfinementProgram.scala new file mode 100644 index 00000000..48ed1770 --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/programs/VorticityConfinementProgram.scala @@ -0,0 +1,152 @@ +package io.computenode.cyfra.fluids.solver.programs + +import io.computenode.cyfra.core.GProgram +import io.computenode.cyfra.core.GProgram.StaticDispatch +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.fluids.solver.* +import io.computenode.cyfra.fluids.solver.utils.GridUtils + +/** Vorticity Confinement Program + * + * Adds vorticity confinement forces to restore small-scale rolling features that are lost due to numerical dissipation. + * + * Based on: Fedkiw et al. "Visual Simulation of Smoke" (SIGGRAPH 2001) and GPU Gems Chapter 38: "Fast Fluid Dynamics Simulation on the GPU" + * + * The algorithm: + * 1. Compute vorticity (curl): ω = ∇ × u + * 2. Compute gradient of vorticity magnitude: ∇|ω| + * 3. Normalize: N = ∇|ω| / |∇|ω|| + * 4. Apply confinement force: f_conf = ε(N × ω)Δt + */ +object VorticityConfinementProgram: + + def create: GProgram[Int, FluidState] = + GProgram[Int, FluidState]( + layout = totalCells => + FluidState( + velocity = GBuffer[Vec4[Float32]](totalCells), + pressure = GBuffer[Float32](totalCells), + density = GBuffer[Float32](totalCells), + temperature = GBuffer[Float32](totalCells), + divergence = GBuffer[Float32](totalCells), + obstacles = GBuffer[Float32](totalCells), + dye = GBuffer[Float32](totalCells), + params = GUniform[FluidParams](), + ), + dispatch = (_, totalCells) => { + val workgroupSize = 256 + val numWorkgroups = (totalCells + workgroupSize - 1) / workgroupSize + StaticDispatch((numWorkgroups, 1, 1)) + }, + workgroupSize = (256, 1, 1), + ): state => + + val idx = GIO.invocationId + val params = state.params.read + val n = params.gridSize + val totalCells = n * n * n + + GIO.when(idx < totalCells): + val (x, y, z) = GridUtils.idxTo3D(idx, n) + + val isInterior = + (x > 0) && + (x < n - 1) && + (y > 0) && + (y < n - 1) && + (z > 0) && + (z < n - 1) + + GIO.when(isInterior): + val velXP = GridUtils.readVec4Safe(state.velocity, x + 1, y, z, n) + val velXM = GridUtils.readVec4Safe(state.velocity, x - 1, y, z, n) + val velYP = GridUtils.readVec4Safe(state.velocity, x, y + 1, z, n) + val velYM = GridUtils.readVec4Safe(state.velocity, x, y - 1, z, n) + val velZP = GridUtils.readVec4Safe(state.velocity, x, y, z + 1, n) + val velZM = GridUtils.readVec4Safe(state.velocity, x, y, z - 1, n) + + val dx = 1.0f + val omegaX = (velYP.z - velYM.z) / (2.0f * dx) - (velZP.y - velZM.y) / (2.0f * dx) + val omegaY = (velZP.x - velZM.x) / (2.0f * dx) - (velXP.z - velXM.z) / (2.0f * dx) + val omegaZ = (velXP.y - velXM.y) / (2.0f * dx) - (velYP.x - velYM.x) / (2.0f * dx) + val omega = vec3(omegaX, omegaY, omegaZ) + + val velXP_YP = GridUtils.readVec4Safe(state.velocity, x + 1, y + 1, z, n) + val velXP_YM = GridUtils.readVec4Safe(state.velocity, x + 1, y - 1, z, n) + val velXP_ZP = GridUtils.readVec4Safe(state.velocity, x + 1, y, z + 1, n) + val velXP_ZM = GridUtils.readVec4Safe(state.velocity, x + 1, y, z - 1, n) + val omegaXP_x = (velXP_YP.z - velXP_YM.z) / (2.0f * dx) - (velXP_ZP.y - velXP_ZM.y) / (2.0f * dx) + val omegaXP_y = (velXP_ZP.x - velXP_ZM.x) / (2.0f * dx) - (velYP.z - velYM.z) / (2.0f * dx) + val omegaXP_z = (velYP.y - velYM.y) / (2.0f * dx) - (velXP_YP.x - velXP_YM.x) / (2.0f * dx) + val magXP = sqrt(omegaXP_x * omegaXP_x + omegaXP_y * omegaXP_y + omegaXP_z * omegaXP_z) + + val velXM_YP = GridUtils.readVec4Safe(state.velocity, x - 1, y + 1, z, n) + val velXM_YM = GridUtils.readVec4Safe(state.velocity, x - 1, y - 1, z, n) + val velXM_ZP = GridUtils.readVec4Safe(state.velocity, x - 1, y, z + 1, n) + val velXM_ZM = GridUtils.readVec4Safe(state.velocity, x - 1, y, z - 1, n) + val omegaXM_x = (velXM_YP.z - velXM_YM.z) / (2.0f * dx) - (velXM_ZP.y - velXM_ZM.y) / (2.0f * dx) + val omegaXM_y = (velXM_ZP.x - velXM_ZM.x) / (2.0f * dx) - (velYM.z - velYP.z) / (2.0f * dx) + val omegaXM_z = (velYM.y - velYP.y) / (2.0f * dx) - (velXM_YP.x - velXM_YM.x) / (2.0f * dx) + val magXM = sqrt(omegaXM_x * omegaXM_x + omegaXM_y * omegaXM_y + omegaXM_z * omegaXM_z) + + val velYP_XP = GridUtils.readVec4Safe(state.velocity, x + 1, y + 1, z, n) + val velYP_XM = GridUtils.readVec4Safe(state.velocity, x - 1, y + 1, z, n) + val velYP_ZP = GridUtils.readVec4Safe(state.velocity, x, y + 1, z + 1, n) + val velYP_ZM = GridUtils.readVec4Safe(state.velocity, x, y + 1, z - 1, n) + val omegaYP_x = (velYP_ZP.z - velYP_ZM.z) / (2.0f * dx) - (velZP.y - velZM.y) / (2.0f * dx) + val omegaYP_y = (velZP.x - velZM.x) / (2.0f * dx) - (velYP_XP.z - velYP_XM.z) / (2.0f * dx) + val omegaYP_z = (velYP_XP.y - velYP_XM.y) / (2.0f * dx) - (velXP.x - velXM.x) / (2.0f * dx) + val magYP = sqrt(omegaYP_x * omegaYP_x + omegaYP_y * omegaYP_y + omegaYP_z * omegaYP_z) + + val velYM_XP = GridUtils.readVec4Safe(state.velocity, x + 1, y - 1, z, n) + val velYM_XM = GridUtils.readVec4Safe(state.velocity, x - 1, y - 1, z, n) + val velYM_ZP = GridUtils.readVec4Safe(state.velocity, x, y - 1, z + 1, n) + val velYM_ZM = GridUtils.readVec4Safe(state.velocity, x, y - 1, z - 1, n) + val omegaYM_x = (velYM_ZP.z - velYM_ZM.z) / (2.0f * dx) - (velZM.y - velZP.y) / (2.0f * dx) + val omegaYM_y = (velZM.x - velZP.x) / (2.0f * dx) - (velYM_XP.z - velYM_XM.z) / (2.0f * dx) + val omegaYM_z = (velYM_XP.y - velYM_XM.y) / (2.0f * dx) - (velXM.x - velXP.x) / (2.0f * dx) + val magYM = sqrt(omegaYM_x * omegaYM_x + omegaYM_y * omegaYM_y + omegaYM_z * omegaYM_z) + + val velZP_XP = GridUtils.readVec4Safe(state.velocity, x + 1, y, z + 1, n) + val velZP_XM = GridUtils.readVec4Safe(state.velocity, x - 1, y, z + 1, n) + val velZP_YP = GridUtils.readVec4Safe(state.velocity, x, y + 1, z + 1, n) + val velZP_YM = GridUtils.readVec4Safe(state.velocity, x, y - 1, z + 1, n) + val omegaZP_x = (velZP_YP.z - velZP_YM.z) / (2.0f * dx) - (velYP.y - velYM.y) / (2.0f * dx) + val omegaZP_y = (velXP.z - velXM.z) / (2.0f * dx) - (velZP_XP.z - velZP_XM.z) / (2.0f * dx) + val omegaZP_z = (velZP_XP.y - velZP_XM.y) / (2.0f * dx) - (velZP_YP.x - velZP_YM.x) / (2.0f * dx) + val magZP = sqrt(omegaZP_x * omegaZP_x + omegaZP_y * omegaZP_y + omegaZP_z * omegaZP_z) + + val velZM_XP = GridUtils.readVec4Safe(state.velocity, x + 1, y, z - 1, n) + val velZM_XM = GridUtils.readVec4Safe(state.velocity, x - 1, y, z - 1, n) + val velZM_YP = GridUtils.readVec4Safe(state.velocity, x, y + 1, z - 1, n) + val velZM_YM = GridUtils.readVec4Safe(state.velocity, x, y - 1, z - 1, n) + val omegaZM_x = (velZM_YP.z - velZM_YM.z) / (2.0f * dx) - (velYM.y - velYP.y) / (2.0f * dx) + val omegaZM_y = (velXM.z - velXP.z) / (2.0f * dx) - (velZM_XP.z - velZM_XM.z) / (2.0f * dx) + val omegaZM_z = (velZM_XP.y - velZM_XM.y) / (2.0f * dx) - (velZM_YP.x - velZM_YM.x) / (2.0f * dx) + val magZM = sqrt(omegaZM_x * omegaZM_x + omegaZM_y * omegaZM_y + omegaZM_z * omegaZM_z) + + val gradMagX = (magXP - magXM) / (2.0f * dx) + val gradMagY = (magYP - magYM) / (2.0f * dx) + val gradMagZ = (magZP - magZM) / (2.0f * dx) + val gradMag = vec3(gradMagX, gradMagY, gradMagZ) + + val gradMagLength = sqrt(gradMagX * gradMagX + gradMagY * gradMagY + gradMagZ * gradMagZ) + val epsilon = 1e-6f + val N = when(gradMagLength > epsilon): + vec3(gradMagX / gradMagLength, gradMagY / gradMagLength, gradMagZ / gradMagLength) + .otherwise: + vec3(0.0f, 0.0f, 0.0f) + + val forceX = N.y * omega.z - N.z * omega.y + val forceY = N.z * omega.x - N.x * omega.z + val forceZ = N.x * omega.y - N.y * omega.x + + val vorticityEpsilon = 0.3f + + val confinementForce = vec3(forceX * vorticityEpsilon, forceY * vorticityEpsilon, forceZ * vorticityEpsilon) + + val vel = state.velocity.read(idx) + val newVel = + vec4(vel.x + confinementForce.x * params.dt, vel.y + confinementForce.y * params.dt, vel.z + confinementForce.z * params.dt, 0.0f) + + GIO.write(state.velocity, idx, newVel) diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/utils/FieldUtils.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/utils/FieldUtils.scala new file mode 100644 index 00000000..3f5e56c5 --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/utils/FieldUtils.scala @@ -0,0 +1,400 @@ +package io.computenode.cyfra.fluids.solver.utils + +import org.lwjgl.BufferUtils + +import java.nio.ByteBuffer + +/** Utilities for initializing and manipulating fluid field buffers on the CPU side. */ +object FieldUtils: + + /** Create empty field buffer initialized with zeros. + * + * @param gridSize + * Grid resolution + * @return + * ByteBuffer containing Float32 values, one per grid cell + */ + def createEmpty(gridSize: Int): ByteBuffer = + val totalCells = gridSize * gridSize * gridSize + val buffer = BufferUtils.createByteBuffer(totalCells * 4) + + for i <- 0 until totalCells do buffer.putFloat(0.0f) + + buffer.flip() + buffer + + /** Set field values to a constant within a spherical region. + * + * @param field + * ByteBuffer to modify (must be rewound after this call) + * @param gridSize + * Grid resolution + * @param centerX + * Sphere center X coordinate + * @param centerY + * Sphere center Y coordinate + * @param centerZ + * Sphere center Z coordinate + * @param radius + * Sphere radius in grid cells + * @param value + * Field value to set (default 1.0) + */ + def addSphere(field: ByteBuffer, gridSize: Int, centerX: Float, centerY: Float, centerZ: Float, radius: Float, value: Float = 1.0f): Unit = + for z <- 0 until gridSize do + for y <- 0 until gridSize do + for x <- 0 until gridSize do + val idx = x + y * gridSize + z * gridSize * gridSize + field.position(idx * 4) + + val dx = x.toFloat - centerX + val dy = y.toFloat - centerY + val dz = z.toFloat - centerZ + val dist = Math.sqrt(dx * dx + dy * dy + dz * dz).toFloat + + if dist <= radius then field.putFloat(value) + + field.position(gridSize * gridSize * gridSize * 4) + field.rewind() + + /** Set field values to a constant within a box region. + * + * @param field + * ByteBuffer to modify + * @param gridSize + * Grid resolution + * @param minX + * Minimum X coordinate (inclusive) + * @param maxX + * Maximum X coordinate (inclusive) + * @param minY + * Minimum Y coordinate (inclusive) + * @param maxY + * Maximum Y coordinate (inclusive) + * @param minZ + * Minimum Z coordinate (inclusive) + * @param maxZ + * Maximum Z coordinate (inclusive) + * @param value + * Field value to set (default 1.0) + */ + def addBox(field: ByteBuffer, gridSize: Int, minX: Int, maxX: Int, minY: Int, maxY: Int, minZ: Int, maxZ: Int, value: Float = 1.0f): Unit = + field.rewind() + + for z <- 0 until gridSize do + for y <- 0 until gridSize do + for x <- 0 until gridSize do + val idx = x + y * gridSize + z * gridSize * gridSize + field.position(idx * 4) + + if x >= minX && x <= maxX && y >= minY && y <= maxY && z >= minZ && z <= maxZ then field.putFloat(value) + + field.rewind() + + /** Set field values to a constant within a cylindrical region (aligned with Y axis). + * + * @param field + * ByteBuffer to modify + * @param gridSize + * Grid resolution + * @param centerX + * Cylinder center X coordinate + * @param centerZ + * Cylinder center Z coordinate + * @param radius + * Cylinder radius in grid cells + * @param minY + * Minimum Y coordinate (inclusive) + * @param maxY + * Maximum Y coordinate (inclusive) + * @param value + * Field value to set (default 1.0) + */ + def addCylinder(field: ByteBuffer, gridSize: Int, centerX: Float, centerZ: Float, radius: Float, minY: Int, maxY: Int, value: Float = 1.0f): Unit = + field.rewind() + + for z <- 0 until gridSize do + for y <- 0 until gridSize do + for x <- 0 until gridSize do + val idx = x + y * gridSize + z * gridSize * gridSize + field.position(idx * 4) + + if y >= minY && y <= maxY then + val dx = x.toFloat + 0.5f - centerX + val dz = z.toFloat + 0.5f - centerZ + val dist = Math.sqrt(dx * dx + dz * dz).toFloat + + if dist <= radius then field.putFloat(value) + + field.rewind() + + /** Set field values to a constant in a boundary region around the grid perimeter. + * + * @param field + * ByteBuffer to modify + * @param gridSize + * Grid resolution + * @param thickness + * Boundary thickness in cells + * @param value + * Field value to set (default 1.0) + */ + def addWalls(field: ByteBuffer, gridSize: Int, thickness: Int = 1, value: Float = 1.0f): Unit = + field.rewind() + + for z <- 0 until gridSize do + for y <- 0 until gridSize do + for x <- 0 until gridSize do + val idx = x + y * gridSize + z * gridSize * gridSize + field.position(idx * 4) + + if x < thickness || x >= gridSize - thickness || y < thickness || y >= gridSize - thickness || z < thickness || z >= gridSize - thickness + then field.putFloat(value) + + field.rewind() + + /** Add a spiral obstacle pattern inspired by Scala logo. + * + * Creates a 3D ribbon-shaped spiral with CONSTANT radius. + * + * RIBBON SHAPE means: + * - WIDE along the curve (tangent direction) + * - THIN perpendicular to the curve in horizontal plane (radial direction) + * - Has VERTICAL HEIGHT + * + * @param obstacles + * Obstacle buffer to modify + * @param gridSize + * Grid resolution + * @param centerX + * Center X position + * @param centerY + * Center Y position + * @param centerZ + * Center Z position + * @param spiralRadius + * Constant radius of the spiral + * @param spiralHeight + * Total height of the spiral + * @param numTurns + * Number of complete rotations + * @param ribbonWidth + * Width along the curve (tangent) + * @param ribbonThickness + * Thickness perpendicular to curve (radial - thin!) + * @param ribbonHeight + * Vertical height of the ribbon + * @param rotationDegrees + * Rotation around Y axis in degrees + * @param value + * Obstacle value (typically 1.0 for solid) + */ + def addSpiralObstacle( + obstacles: ByteBuffer, + gridSize: Int, + centerX: Float, + centerY: Float, + centerZ: Float, + spiralRadius: Float, + spiralHeight: Float, + numTurns: Float = 2.5f, + ribbonWidth: Float, + ribbonThickness: Float, + ribbonHeight: Float, + rotationDegrees: Float = 0.0f, + value: Float = 1.0f, + ): Unit = + val numPoints = 300 + val angleStep = (numTurns * 2.0f * Math.PI.toFloat) / numPoints + val rotationRad = rotationDegrees * Math.PI.toFloat / 180.0f + val cosRot = Math.cos(rotationRad).toFloat + val sinRot = Math.sin(rotationRad).toFloat + + for i <- 0 until numPoints do + val t = i.toFloat / numPoints.toFloat + + val angle = -(i * angleStep) + + val spiralX = Math.cos(angle).toFloat * spiralRadius + val spiralZ = Math.sin(angle).toFloat * spiralRadius + val spiralY = spiralHeight * t + + val localX = spiralX * cosRot - spiralZ * sinRot + val localZ = spiralX * sinRot + spiralZ * cosRot + + val x = centerX + localX + val z = centerZ + localZ + val y = centerY + spiralY + + val tangentAngle = angle + Math.PI.toFloat / 2.0f + val localTangentX = Math.cos(tangentAngle).toFloat + val localTangentZ = Math.sin(tangentAngle).toFloat + + val tangentX = localTangentX * cosRot - localTangentZ * sinRot + val tangentZ = localTangentX * sinRot + localTangentZ * cosRot + + val radialX = spiralX / spiralRadius + val radialZ = spiralZ / spiralRadius + val worldRadialX = radialX * cosRot - radialZ * sinRot + val worldRadialZ = radialX * sinRot + radialZ * cosRot + + val halfWidth = ribbonWidth / 2.0f + val halfThickness = ribbonThickness / 2.0f + val halfHeight = ribbonHeight / 2.0f + + val corners = Seq( + (-halfWidth, -halfThickness, -halfHeight), + (-halfWidth, -halfThickness, +halfHeight), + (-halfWidth, +halfThickness, -halfHeight), + (-halfWidth, +halfThickness, +halfHeight), + (+halfWidth, -halfThickness, -halfHeight), + (+halfWidth, -halfThickness, +halfHeight), + (+halfWidth, +halfThickness, -halfHeight), + (+halfWidth, +halfThickness, +halfHeight), + ) + + var minWorldX = Float.MaxValue + var maxWorldX = Float.MinValue + var minWorldY = Float.MaxValue + var maxWorldY = Float.MinValue + var minWorldZ = Float.MaxValue + var maxWorldZ = Float.MinValue + + for (tangentOffset, radialOffset, verticalOffset) <- corners do + val worldX = x + tangentX * tangentOffset + worldRadialX * radialOffset + val worldY = y + verticalOffset + val worldZ = z + tangentZ * tangentOffset + worldRadialZ * radialOffset + + minWorldX = minWorldX min worldX + maxWorldX = maxWorldX max worldX + minWorldY = minWorldY min worldY + maxWorldY = maxWorldY max worldY + minWorldZ = minWorldZ min worldZ + maxWorldZ = maxWorldZ max worldZ + + val minXi = minWorldX.toInt max 0 + val maxXi = maxWorldX.toInt min (gridSize - 1) + val minYi = minWorldY.toInt max 0 + val maxYi = maxWorldY.toInt min (gridSize - 1) + val minZi = minWorldZ.toInt max 0 + val maxZi = maxWorldZ.toInt min (gridSize - 1) + + if minXi <= maxXi && minYi <= maxYi && minZi <= maxZi then + addBox(obstacles, gridSize, minX = minXi, maxX = maxXi, minY = minYi, maxY = maxYi, minZ = minZi, maxZ = maxZi, value = value) + + /** Add a disc perpendicular to X axis (circular in YZ plane) - for scalar fields. + * + * Creates a thin disc that faces along the X direction. + * + * @param buffer + * Field buffer to modify (Float32 buffer) + * @param gridSize + * Grid resolution + * @param centerX + * Center X position + * @param centerY + * Center Y position + * @param centerZ + * Center Z position + * @param radius + * Disc radius (in YZ plane) + * @param thickness + * Disc thickness (in X direction) + * @param value + * Field value to set + */ + def addDiscPerpToX( + buffer: ByteBuffer, + gridSize: Int, + centerX: Float, + centerY: Float, + centerZ: Float, + radius: Float, + thickness: Float, + value: Float, + ): Unit = + buffer.rewind() + val halfThickness = thickness / 2.0f + + for z <- 0 until gridSize do + for y <- 0 until gridSize do + for x <- 0 until gridSize do + val dx = x.toFloat - centerX + if Math.abs(dx) <= halfThickness then + val dy = y.toFloat - centerY + val dz = z.toFloat - centerZ + val distYZ = Math.sqrt(dy * dy + dz * dz).toFloat + + if distYZ <= radius then + val idx = x + y * gridSize + z * gridSize * gridSize + buffer.position(idx * 4) + val existingValue = buffer.getFloat(idx * 4) + buffer.position(idx * 4) + buffer.putFloat(existingValue + value) + + buffer.rewind() + + /** Add velocity in a disc perpendicular to X axis (circular in YZ plane) - for Vec4 velocity fields. + * + * Creates a thin disc with velocity that faces along the X direction. + * + * @param velocityBuffer + * Velocity field buffer to modify (Vec4[Float32] = 16 bytes per cell) + * @param gridSize + * Grid resolution + * @param centerX + * Center X position + * @param centerY + * Center Y position + * @param centerZ + * Center Z position + * @param radius + * Disc radius (in YZ plane) + * @param thickness + * Disc thickness (in X direction) + * @param velocityX + * Velocity X component + * @param velocityY + * Velocity Y component + * @param velocityZ + * Velocity Z component + */ + def addDiscVecPerpToX( + velocityBuffer: ByteBuffer, + gridSize: Int, + centerX: Float, + centerY: Float, + centerZ: Float, + radius: Float, + thickness: Float, + velocityX: Float, + velocityY: Float, + velocityZ: Float, + ): Unit = + velocityBuffer.rewind() + val halfThickness = thickness / 2.0f + + for z <- 0 until gridSize do + for y <- 0 until gridSize do + for x <- 0 until gridSize do + val dx = x.toFloat - centerX + if Math.abs(dx) <= halfThickness then + val dy = y.toFloat - centerY + val dz = z.toFloat - centerZ + val distYZ = Math.sqrt(dy * dy + dz * dz).toFloat + + if distYZ <= radius then + val idx = x + y * gridSize + z * gridSize * gridSize + velocityBuffer.position(idx * 16) + + val existingX = velocityBuffer.getFloat() + val existingY = velocityBuffer.getFloat() + val existingZ = velocityBuffer.getFloat() + + velocityBuffer.position(idx * 16) + velocityBuffer.putFloat(existingX + velocityX) + velocityBuffer.putFloat(existingY + velocityY) + velocityBuffer.putFloat(existingZ + velocityZ) + velocityBuffer.putFloat(0.0f) + + velocityBuffer.rewind() diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/utils/GridUtils.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/utils/GridUtils.scala new file mode 100644 index 00000000..e589c627 --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/utils/GridUtils.scala @@ -0,0 +1,127 @@ +package io.computenode.cyfra.fluids.solver.utils + +import io.computenode.cyfra.dsl.{*, given} + +/** Utility functions for 3D grid operations in GPU shaders. */ +object GridUtils: + + /** Convert 3D coordinates to 1D flattened index. Uses row-major order: index = x + y*N + z*N² + */ + inline def coord3dToIdx(x: Int32, y: Int32, z: Int32, n: Int32): Int32 = + x + y * n + z * n * n + + def idxTo3D(idx: Int32, n: Int32): (Int32, Int32, Int32) = + val z = idx / (n * n) + val y = (idx / n).mod(n) + val x = idx.mod(n) + (x, y, z) + + /** Check if 3D coordinates are within grid bounds */ + inline def inBounds(x: Int32, y: Int32, z: Int32, n: Int32): GBoolean = + (x >= 0) && + (x < n) && + (y >= 0) && + (y < n) && + (z >= 0) && + (z < n) + + /** Min for Int32 (Functions.min only supports Float32) */ + inline def minInt32(a: Int32, b: Int32)(using Source): Int32 = + when(a < b)(a).otherwise(b) + + /** Max for Int32 (Functions.max only supports Float32) */ + inline def maxInt32(a: Int32, b: Int32)(using Source): Int32 = + when(a > b)(a).otherwise(b) + + /** Read Vec4 from buffer with bounds checking, return zero if out of bounds */ + def readVec4Safe(buffer: GBuffer[Vec4[Float32]], x: Int32, y: Int32, z: Int32, n: Int32)(using Source): Vec4[Float32] = + val xClamped = maxInt32(0, minInt32(x, n - 1)) + val yClamped = maxInt32(0, minInt32(y, n - 1)) + val zClamped = maxInt32(0, minInt32(z, n - 1)) + buffer.read(coord3dToIdx(xClamped, yClamped, zClamped, n)) + + /** Read scalar from buffer with bounds checking */ + def readFloat32Safe(buffer: GBuffer[Float32], x: Int32, y: Int32, z: Int32, n: Int32)(using Source): Float32 = + val xClamped = maxInt32(0, minInt32(x, n - 1)) + val yClamped = maxInt32(0, minInt32(y, n - 1)) + val zClamped = maxInt32(0, minInt32(z, n - 1)) + buffer.read(coord3dToIdx(xClamped, yClamped, zClamped, n)) + + /** Trilinear interpolation for Vec4 field. Samples 8 surrounding grid points and blends them. Note: pos only uses x,y,z components + */ + def trilinearInterpolateVec4(buffer: GBuffer[Vec4[Float32]], pos: Vec3[Float32], size: Int32)(using Source): Vec4[Float32] = + val maxPos = (size - 1).asFloat + val x = clamp(pos.x, 0.0f, maxPos) + val y = clamp(pos.y, 0.0f, maxPos) + val z = clamp(pos.z, 0.0f, maxPos) + + val x0 = x.asInt + val y0 = y.asInt + val z0 = z.asInt + val x1 = minInt32(x0 + 1, size - 1) + val y1 = minInt32(y0 + 1, size - 1) + val z1 = minInt32(z0 + 1, size - 1) + + val fx = x - x0.asFloat + val fy = y - y0.asFloat + val fz = z - z0.asFloat + + val v000 = readVec4Safe(buffer, x0, y0, z0, size) + val v100 = readVec4Safe(buffer, x1, y0, z0, size) + val v010 = readVec4Safe(buffer, x0, y1, z0, size) + val v110 = readVec4Safe(buffer, x1, y1, z0, size) + val v001 = readVec4Safe(buffer, x0, y0, z1, size) + val v101 = readVec4Safe(buffer, x1, y0, z1, size) + val v011 = readVec4Safe(buffer, x0, y1, z1, size) + val v111 = readVec4Safe(buffer, x1, y1, z1, size) + + val fxVec = vec4(fx, fx, fx, fx) + val fyVec = vec4(fy, fy, fy, fy) + val fzVec = vec4(fz, fz, fz, fz) + + val v00 = mix(v000, v100, fxVec) + val v10 = mix(v010, v110, fxVec) + val v01 = mix(v001, v101, fxVec) + val v11 = mix(v011, v111, fxVec) + + val v0 = mix(v00, v10, fyVec) + val v1 = mix(v01, v11, fyVec) + + mix(v0, v1, fzVec) + + /** Trilinear interpolation for Float32 field */ + def trilinearInterpolateFloat32(buffer: GBuffer[Float32], pos: Vec3[Float32], size: Int32)(using Source): Float32 = + val maxPos = (size - 1).asFloat + val x = clamp(pos.x, 0.0f, maxPos) + val y = clamp(pos.y, 0.0f, maxPos) + val z = clamp(pos.z, 0.0f, maxPos) + + val x0 = x.asInt + val y0 = y.asInt + val z0 = z.asInt + val x1 = minInt32(x0 + 1, size - 1) + val y1 = minInt32(y0 + 1, size - 1) + val z1 = minInt32(z0 + 1, size - 1) + + val fx = x - x0.asFloat + val fy = y - y0.asFloat + val fz = z - z0.asFloat + + val v000 = readFloat32Safe(buffer, x0, y0, z0, size) + val v100 = readFloat32Safe(buffer, x1, y0, z0, size) + val v010 = readFloat32Safe(buffer, x0, y1, z0, size) + val v110 = readFloat32Safe(buffer, x1, y1, z0, size) + val v001 = readFloat32Safe(buffer, x0, y0, z1, size) + val v101 = readFloat32Safe(buffer, x1, y0, z1, size) + val v011 = readFloat32Safe(buffer, x0, y1, z1, size) + val v111 = readFloat32Safe(buffer, x1, y1, z1, size) + + val v00 = mix(v000, v100, fx) + val v10 = mix(v010, v110, fx) + val v01 = mix(v001, v101, fx) + val v11 = mix(v011, v111, fx) + + val v0 = mix(v00, v10, fy) + val v1 = mix(v01, v11, fy) + + mix(v0, v1, fz) diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/utils/ObstacleUtils.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/utils/ObstacleUtils.scala new file mode 100644 index 00000000..dd6490b4 --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/solver/utils/ObstacleUtils.scala @@ -0,0 +1,63 @@ +package io.computenode.cyfra.fluids.solver.utils + +import io.computenode.cyfra.dsl.{*, given} +import org.lwjgl.BufferUtils + +import java.nio.ByteBuffer + +/** Utilities for creating and manipulating obstacle geometry in the fluid grid. + * + * Obstacles are represented as a grid of Float32 values: + * - 0 or negative: Fluid cell (no obstacle) + * - Positive: Solid cell (obstacle), value encodes color/material (0.0-1.0 range) + */ +object ObstacleUtils: + + /** Check if a cell is a solid obstacle with bounds checking (returns false if out of bounds) */ + inline def isSolid(obstacles: GBuffer[Float32], idx: Int32, totalCells: Int32)(using io.computenode.cyfra.dsl.macros.Source): GBoolean = + when(idx >= 0): + when(idx < totalCells): + obstacles.read(idx) > 0.0f + .otherwise: + false + .otherwise: + false + + /** Check if a 3D coordinate is inside a solid obstacle with bounds checking. Returns false if coordinates are out of bounds. + */ + inline def isSolidAt(obstacles: GBuffer[Float32], x: Int32, y: Int32, z: Int32, n: Int32)(using io.computenode.cyfra.dsl.macros.Source): GBoolean = + when(GridUtils.inBounds(x, y, z, n)): + isSolid(obstacles, GridUtils.coord3dToIdx(x, y, z, n), n * n * n) + .otherwise: + false + + /** Get obstacle color value (0.0-1.0, returns 0 if not solid). Note: Does not perform bounds checking. + */ + inline def getObstacleValue(obstacles: GBuffer[Float32], idx: Int32)(using io.computenode.cyfra.dsl.macros.Source): Float32 = + max(0.0f, obstacles.read(idx)) + + /** Get obstacle color value with bounds checking (returns 0 if out of bounds or not solid) */ + inline def getObstacleValueSafe(obstacles: GBuffer[Float32], idx: Int32, totalCells: Int32)(using io.computenode.cyfra.dsl.macros.Source): Float32 = + when((idx >= 0) && (idx < totalCells)): + max(0.0f, obstacles.read(idx)) + .otherwise: + 0.0f + + /** Compute surface normal for obstacle visualization (GPU side). + * + * Uses central differences to estimate the gradient of the obstacle field. Returns normalized vector pointing away from solid. + */ + def computeNormal(obstacles: GBuffer[Float32], x: Int32, y: Int32, z: Int32, n: Int32)(using + io.computenode.cyfra.dsl.macros.Source, + ): Vec3[Float32] = + + val xp = when(isSolidAt(obstacles, x + 1, y, z, n))(1.0f).otherwise(0.0f) + val xn = when(isSolidAt(obstacles, x - 1, y, z, n))(1.0f).otherwise(0.0f) + val yp = when(isSolidAt(obstacles, x, y + 1, z, n))(1.0f).otherwise(0.0f) + val yn = when(isSolidAt(obstacles, x, y - 1, z, n))(1.0f).otherwise(0.0f) + val zp = when(isSolidAt(obstacles, x, y, z + 1, n))(1.0f).otherwise(0.0f) + val zn = when(isSolidAt(obstacles, x, y, z - 1, n))(1.0f).otherwise(0.0f) + + val grad = vec3(xp - xn, yp - yn, zp - zn) + + normalize(grad) diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/visualization/Camera3D.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/visualization/Camera3D.scala new file mode 100644 index 00000000..37b6a6d3 --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/visualization/Camera3D.scala @@ -0,0 +1,45 @@ +package io.computenode.cyfra.fluids.visualization + +import io.computenode.cyfra.dsl.{*, given} + +/** Camera parameters for 3D rendering. + * + * Uses Vec4 instead of Vec3 for proper 16-byte alignment in GPU memory. The w component is unused for position/target/up vectors. + * + * @param position + * Camera position in world space (w unused) + * @param target + * Point the camera is looking at (w unused) + * @param up + * Up vector (typically (0, 1, 0, 0)) (w unused) + * @param fov + * Field of view in degrees + * @param aspectRatio + * Width / height ratio + */ +case class Camera3D(position: Vec4[Float32], target: Vec4[Float32], up: Vec4[Float32], fov: Float32, aspectRatio: Float32) extends GStruct[Camera3D] + +object Camera3D: + /** Create a default camera looking at the origin from (0, 0, 5) */ + def default(aspectRatio: Float): Camera3D = Camera3D( + position = (0.0f, 0.0f, 5.0f, 0.0f), // Vec4, w unused + target = (0.0f, 0.0f, 0.0f, 0.0f), + up = (0.0f, 1.0f, 0.0f, 0.0f), + fov = 45.0f, + aspectRatio = aspectRatio, + ) + + /** Create a camera orbiting around a center point */ + def orbit(centerX: Float, centerY: Float, centerZ: Float, radius: Float, angle: Float, height: Float, aspectRatio: Float): Camera3D = + import scala.math.{cos, sin} + // Compute ALL values on host side before creating tuple + val x = centerX + radius * cos(angle).toFloat + val y = centerY + height + val z = centerZ + radius * sin(angle).toFloat + Camera3D( + position = (x, y, z, 0.0f), // Vec4 with w=0 + target = (centerX, centerY, centerZ, 0.0f), + up = (0.0f, 1.0f, 0.0f, 0.0f), + fov = 45.0f, + aspectRatio = aspectRatio, + ) diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/visualization/FluidColorMap.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/visualization/FluidColorMap.scala new file mode 100644 index 00000000..5fced818 --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/visualization/FluidColorMap.scala @@ -0,0 +1,76 @@ +package io.computenode.cyfra.fluids.visualization + +import io.computenode.cyfra.dsl.{*, given} + +/** Utility functions for mapping fluid properties to colors. */ +object FluidColorMap: + + /** Simple grayscale mapping based on density. + * + * @param density + * Fluid density value (0.0 to 1.0) + * @return + * RGBA color with density as grayscale + */ + def grayscale(density: Float32)(using Source): Vec4[Float32] = + val clamped = clamp(density, 0.0f, 1.0f) + vec4(clamped, clamped, clamped, clamped) + + /** Temperature-based color ramp (cold blue to hot red). + * + * Maps density to a heat map: + * - 0.0 = black + * - 0.2 = dark blue + * - 0.4 = cyan + * - 0.6 = yellow + * - 0.8 = orange + * - 1.0 = white + * + * @param density + * Fluid density value + * @return + * RGBA color on the heat map + */ + def heatMap(density: Float32)(using Source): Vec4[Float32] = + val d = clamp(density, 0.0f, 1.0f) + + // Piecewise linear color ramp + val r = when(d < 0.5f)(d * 2.0f).otherwise(1.0f) + val g = when(d < 0.25f)(0.0f).otherwise(when(d < 0.75f)((d - 0.25f) * 2.0f).otherwise(1.0f)) + val b = when(d < 0.5f)(1.0f - d * 2.0f).otherwise(0.0f) + + vec4(r, g, b, 1.0f) + + /** Smoke-like appearance with soft falloff. + * + * Creates a smoky white appearance with soft edges. + * + * @param density + * Fluid density value + * @return + * RGBA color with alpha for blending + */ + def smoke(density: Float32)(using Source): Vec4[Float32] = + val d = clamp(density, 0.0f, 1.0f) + val brightness = sqrt(d) // Gamma correction for softer appearance + val alpha = d * 0.8f // Not fully opaque + vec4(brightness, brightness, brightness, 1.0f) + + /** Velocity magnitude-based coloring. + * + * Colors based on velocity magnitude: + * - Slow = blue/cold + * - Fast = red/hot + * + * @param velocity + * Velocity vector + * @param maxSpeed + * Maximum expected speed for normalization + * @return + * RGBA color representing speed + */ + def velocityMagnitude(velocity: Vec4[Float32], maxSpeed: Float32)(using Source): Vec4[Float32] = + val vel3 = vec3(velocity.x, velocity.y, velocity.z) + val speed = sqrt(vel3 dot vel3) + val normalized = clamp(speed / maxSpeed, 0.0f, 1.0f) + heatMap(normalized) diff --git a/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/visualization/RayMarchRenderer.scala b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/visualization/RayMarchRenderer.scala new file mode 100644 index 00000000..29f14f61 --- /dev/null +++ b/cyfra-fluids/src/main/scala/io/computenode/cyfra/fluids/visualization/RayMarchRenderer.scala @@ -0,0 +1,347 @@ +package io.computenode.cyfra.fluids.visualization + +import io.computenode.cyfra.core.{GBufferRegion, GCodec, GProgram} +import io.computenode.cyfra.core.GProgram.StaticDispatch +import io.computenode.cyfra.core.GCodec.{*, given} +import io.computenode.cyfra.core.layout.Layout +import io.computenode.cyfra.runtime.VkCyfraRuntime +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.fluids.solver.utils.{GridUtils, ObstacleUtils} +import org.lwjgl.BufferUtils + +import java.nio.ByteBuffer +import java.nio.ByteOrder +import RayMarchRenderer.* +import GridUtils.* + +/** Volume ray marching renderer for fluid visualization. + * + * Renders 3D fluid density using ray marching with opacity accumulation. + * + * @param width + * Image width in pixels + * @param height + * Image height in pixels + * @param runtime + * Cyfra runtime for GPU execution + */ +class RayMarchRenderer(rendererConfig: RendererConfig): + + private val width = rendererConfig.width + private val height = rendererConfig.height + + /** Compute ray-box intersection and return entry distance. Returns -1 if no intersection. + */ + private def rayBoxIntersection(origin: Vec3[Float32], direction: Vec3[Float32], boxMin: Vec3[Float32], boxMax: Vec3[Float32]): Float32 = + // Compute inverse direction (infinity/NaN handled by min/max) + val invDirX = 1.0f / direction.x + val invDirY = 1.0f / direction.y + val invDirZ = 1.0f / direction.z + + // Compute intersection t values for each slab + val t1x = (boxMin.x - origin.x) * invDirX + val t2x = (boxMax.x - origin.x) * invDirX + val t1y = (boxMin.y - origin.y) * invDirY + val t2y = (boxMax.y - origin.y) * invDirY + val t1z = (boxMin.z - origin.z) * invDirZ + val t2z = (boxMax.z - origin.z) * invDirZ + + // Find min/max for each axis + val tminx = min(t1x, t2x) + val tmaxx = max(t1x, t2x) + val tminy = min(t1y, t2y) + val tmaxy = max(t1y, t2y) + val tminz = min(t1z, t2z) + val tmaxz = max(t1z, t2z) + + // Find overall entry and exit distances + val tNear = max(max(tminx, tminy), tminz) + val tFar = min(min(tmaxx, tmaxy), tmaxz) + + // Check for valid intersection + when((tFar < 0.0f) || (tNear > tFar)): + -1.0f // No intersection + .otherwise: + max(tNear, 0.0f) // Entry distance (clamp to 0 if inside box) + + /** March along a ray and accumulate color/opacity */ + private def marchRay( + origin: Vec3[Float32], + direction: Vec3[Float32], + velocityBuffer: GBuffer[Vec4[Float32]], + pressureBuffer: GBuffer[Float32], + densityBuffer: GBuffer[Float32], + temperatureBuffer: GBuffer[Float32], + dyeBuffer: GBuffer[Float32], + obstaclesBuffer: GBuffer[Float32], + gridSize: Int32, + ): Vec4[Float32] = + val maxSteps = 2048 + val stepSize = 0.15f + val absorptionCoeff = 0.3f + val transmittanceThreshold = 0.01f + + // Define grid bounding box + val boxMin = vec3(0.0f, 0.0f, 0.0f) + val boxMax = vec3(gridSize.asFloat, gridSize.asFloat, gridSize.asFloat) + + // Find where ray enters the volume + val entryDist = rayBoxIntersection(origin, direction, boxMin, boxMax) + + // Background color + val backgroundColor = vec4(0.05f, 0.05f, 0.1f, 1.0f) + + // If ray doesn't intersect volume, return background + when(entryDist < 0.0f): + backgroundColor + .otherwise: + // Start marching from entry point + val startPos = origin + direction * entryDist + val maxDistance = gridSize.asFloat * 3.0f + + val initState = RayMarchState(pos = startPos, accumColor = vec4(0.0f, 0.0f, 0.0f, 0.0f), transmittance = 1.0f, t = entryDist) + + val finalState = GSeq + .gen[RayMarchState]( + first = initState, + next = state => + + val nextPos = state.pos + direction * stepSize + val nextT = state.t + stepSize + + // Check if ray is still inside the grid volume (continuous bounds check) + val gridMax = gridSize.asFloat + val posInBounds = + (state.pos.x >= 0.0f) && + (state.pos.x <= gridMax) && + (state.pos.y >= 0.0f) && + (state.pos.y <= gridMax) && + (state.pos.z >= 0.0f) && + (state.pos.z <= gridMax) + + // Check if next position will be outside (to stop BEFORE exiting) + val nextPosInBounds = + (nextPos.x >= 0.0f) && + (nextPos.x <= gridMax) && + (nextPos.y >= 0.0f) && + (nextPos.y <= gridMax) && + (nextPos.z >= 0.0f) && + (nextPos.z <= gridMax) + + // Check if we're inside an obstacle (only if in bounds) + val cellX = state.pos.x.asInt + val cellY = state.pos.y.asInt + val cellZ = state.pos.z.asInt + val cellInBounds = + (cellX >= 0) && + (cellX < gridSize) && + (cellY >= 0) && + (cellY < gridSize) && + (cellZ >= 0) && + (cellZ < gridSize) + val cellIdx = coord3dToIdx(cellX, cellY, cellZ, gridSize) + val totalCells = gridSize * gridSize * gridSize + val hitObstacle = cellInBounds && ObstacleUtils.isSolid(obstaclesBuffer, cellIdx, totalCells) + + when(hitObstacle && rendererConfig.renderObstacles): + // Get obstacle color/brightness value + val obstacleValue = ObstacleUtils.getObstacleValue(obstaclesBuffer, cellIdx) + + // Simple ambient + diffuse lighting for obstacle + val lightDir = normalize(vec3(-1f, -1f, -1f)) + val normal = ObstacleUtils.computeNormal(obstaclesBuffer, cellX, cellY, cellZ, gridSize) + val diffuse = max(0.0f, normal dot lightDir) + val ambient = 0.3f + val brightness = clamp(ambient + diffuse * 0.7f, 0.0f, 1.0f) + + val sampleColor = vec4(brightness * 1f, brightness * 0.3f, brightness * 0.3f * 1.1f, 1.0f) + + val colorContribution = sampleColor * state.transmittance + val nextColor = state.accumColor + colorContribution + + val nextState = + when(state.state === MarchState.LAST_STEP)(MarchState.DONE) + .otherwise(MarchState.LAST_STEP) + RayMarchState(nextPos, nextColor, 0f, nextT, nextState) + .otherwise: + val rescaleFactor = rendererConfig.renderMax - rendererConfig.renderOver + val (sampleColor, opacity) = rendererConfig.fieldToRender match + case Field.Density => + val density = trilinearInterpolateFloat32(densityBuffer, state.pos, gridSize) + val clamped = clamp(density - rendererConfig.renderOver, 0.0f, rendererConfig.renderMax) / rescaleFactor + (FluidColorMap.heatMap(clamped), clamped) + case Field.Pressure => + val pressure = trilinearInterpolateFloat32(pressureBuffer, state.pos, gridSize) + val clamped = clamp(pressure - rendererConfig.renderOver, 0.0f, rendererConfig.renderMax) / rescaleFactor + (FluidColorMap.heatMap(clamped), clamped) + case Field.Temperature => + val temperature = trilinearInterpolateFloat32(temperatureBuffer, state.pos, gridSize) + val clamped = clamp(temperature - rendererConfig.renderOver, 0.0f, rendererConfig.renderMax) / rescaleFactor + (FluidColorMap.heatMap(clamped), clamped) + case Field.Dye => + val dye = trilinearInterpolateFloat32(dyeBuffer, state.pos, gridSize) + val clamped = clamp(dye - rendererConfig.renderOver, 0.0f, rendererConfig.renderMax) / rescaleFactor + (FluidColorMap.heatMap(clamped), clamped) + case Field.Velocity => + val velocity = abs(trilinearInterpolateVec4(velocityBuffer, state.pos, gridSize)) + val velLen = length(velocity.xyz) + val clamped = clamp(velLen - rendererConfig.renderOver, 0.0f, rendererConfig.renderMax) / rescaleFactor + (FluidColorMap.heatMap(clamped), clamped) + + val alpha = clamp(opacity * absorptionCoeff, 0.0f, 1.0f) + + // Accumulate color with current transmittance + val colorContribution = sampleColor * alpha * state.transmittance + val nextColor = state.accumColor + colorContribution + + // Update transmittance + val nextTransmittance = state.transmittance * (1.0f - alpha) + + // Check if ray should terminate (stop if next step would exit volume) + val shouldFinish = (!nextPosInBounds) || (nextTransmittance < transmittanceThreshold) || (nextT > maxDistance) + val nextState = + when(state.state === MarchState.LAST_STEP)(MarchState.DONE) + .elseWhen(hitObstacle)(MarchState.LAST_STEP) + .elseWhen(shouldFinish)(MarchState.DONE) + .otherwise(MarchState.MARCHING) + RayMarchState(nextPos, nextColor, nextTransmittance, nextT, nextState), + ) + .limit(maxSteps) + .takeWhile(_.state !== MarchState.DONE) + .lastOr(initState) + + // Add background with remaining transmittance + finalState.accumColor + backgroundColor * finalState.transmittance + + /** Generate ray direction from camera through pixel (returns just direction) */ + private def generateRayDirection(x: Int32, y: Int32, camera: Camera3D): Vec3[Float32] = + // Normalize pixel coordinates to [-1, 1] + val aspectRatio = width.toFloat / height.toFloat + val u = (x.asFloat / width.toFloat) * 2.0f - 1.0f + val v = ((y.asFloat / height.toFloat) * 2.0f - 1.0f) / aspectRatio + + // Extract Vec3 from Vec4 camera vectors (ignore w component) + val pos3 = vec3(camera.position.x, camera.position.y, camera.position.z) + val target3 = vec3(camera.target.x, camera.target.y, camera.target.z) + val up3 = vec3(camera.up.x, camera.up.y, camera.up.z) + + // Camera basis vectors + val forward = normalize(target3 - pos3) + val right = normalize(cross(forward, up3)) + val up = cross(right, forward) + + // Calculate ray direction based on FOV + val fovRad = camera.fov * 3.14159265f / 180.0f + val cameraDist = 1.0f / tan(fovRad * 0.5f) + val rayTarget = (right * u) + (up * v) + (forward * cameraDist) + normalize[Vec3[Float32]](rayTarget) + + /** Rendering program */ + val renderProgram = GProgram[Int, RenderLayout]( + layout = totalCells => + RenderLayout( + output = GBuffer[Vec4[Float32]](width * height), + velocity = GBuffer[Vec4[Float32]](totalCells), + pressure = GBuffer[Float32](totalCells), + density = GBuffer[Float32](totalCells), + temperature = GBuffer[Float32](totalCells), + dye = GBuffer[Float32](totalCells), + obstacles = GBuffer[Float32](totalCells), + camera = GUniform[Camera3D](), + params = GUniform[RenderParams](), + ), + dispatch = (layout, _) => { + val totalPixels = width * height + val workgroupSize = 256 + val numWorkgroups = (totalPixels + workgroupSize - 1) / workgroupSize + StaticDispatch((numWorkgroups, 1, 1)) + }, + workgroupSize = (256, 1, 1), + ): layout => + val idx = GIO.invocationId + val totalPixels = width * height + + GIO.when(idx < totalPixels): + // Convert 1D index to 2D pixel coordinates + val y = idx / width + val x = idx.mod(width) + + // Read camera and params + val cam = layout.camera.read + val params = layout.params.read + + // Generate ray for this pixel + val rayDirection = generateRayDirection(x, y, cam) + + // Extract camera position as Vec3 (ignore w) + val camPos = vec3(cam.position.x, cam.position.y, cam.position.z) + + // March along ray and accumulate color + val finalColor = marchRay( + camPos, + rayDirection, + layout.velocity, + layout.pressure, + layout.density, + layout.temperature, + layout.dye, + layout.obstacles, + params.gridSize, + ) + + for _ <- GIO.write(layout.output, idx, finalColor) + yield GStruct.Empty() + + /** Helper to clamp float values (CPU version) */ + private def clampFloat(value: Float, min: Float, max: Float): Float = + if value < min then min + else if value > max then max + else value + +object RayMarchRenderer: + + case class RendererConfig( + width: Int, + height: Int, + fieldToRender: Field, + renderOver: Float = 0f, + renderMax: Float = 1f, + renderObstacles: Boolean = true, + ) + + enum Field: + case Velocity + case Pressure + case Density + case Temperature + case Dye + + object MarchState: + val MARCHING: Int32 = 0 + val LAST_STEP: Int32 = 1 + val DONE: Int32 = 2 + + /** Ray marching state for accumulation along ray */ + private case class RayMarchState( + pos: Vec3[Float32], + accumColor: Vec4[Float32], + transmittance: Float32, + t: Float32, + state: Int32 = MarchState.MARCHING, + ) extends GStruct[RayMarchState] + + /** Parameters for rendering */ + case class RenderParams(gridSize: Int32) extends GStruct[RenderParams] + + /** Layout for rendering. */ + case class RenderLayout( + output: GBuffer[Vec4[Float32]], + velocity: GBuffer[Vec4[Float32]], + pressure: GBuffer[Float32], + density: GBuffer[Float32], + temperature: GBuffer[Float32], + dye: GBuffer[Float32], + obstacles: GBuffer[Float32], + camera: GUniform[Camera3D], + params: GUniform[RenderParams], + ) derives Layout diff --git a/cyfra-fluids/src/test/resources/log4j2.xml b/cyfra-fluids/src/test/resources/log4j2.xml new file mode 100644 index 00000000..b3b70251 --- /dev/null +++ b/cyfra-fluids/src/test/resources/log4j2.xml @@ -0,0 +1,16 @@ + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/AdvectionProgramTest.scala b/cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/AdvectionProgramTest.scala new file mode 100644 index 00000000..624aaf36 --- /dev/null +++ b/cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/AdvectionProgramTest.scala @@ -0,0 +1,123 @@ +package io.computenode.cyfra.fluids.solver + +import io.computenode.cyfra.core.GBufferRegion +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.fluids.solver.{FluidParams, FluidStateDouble} +import io.computenode.cyfra.fluids.solver.programs.AdvectionProgram +import io.computenode.cyfra.runtime.VkCyfraRuntime + +import java.nio.{ByteBuffer, ByteOrder} + +class AdvectionProgramTest extends munit.FunSuite: + + var runtime: VkCyfraRuntime = null + + override def beforeAll(): Unit = + runtime = VkCyfraRuntime() + + override def afterAll(): Unit = + if runtime != null then runtime.close() + + test("AdvectionProgram transports density along velocity field"): + val gridSize = 32 + val totalCells = gridSize * gridSize * gridSize + + // Create fluid parameters + val params = FluidParams( + dt = 0.3f, + viscosity = 0.0001f, + diffusion = 0.0001f, + buoyancy = 8.0f, + ambient = 0.0f, + gridSize = gridSize, + windX = 0.0f, + windY = 0f, + windZ = 0.0f, + ) + + val paramsBuffer = { + import io.computenode.cyfra.core.GCodec + import io.computenode.cyfra.dsl.struct.GStruct.given + import io.computenode.cyfra.spirv.compilers.SpirvProgramCompiler.totalStride + + val schema = summon[io.computenode.cyfra.dsl.struct.GStructSchema[FluidParams]] + val size = totalStride(schema) + val buffer = ByteBuffer.allocateDirect(size).order(ByteOrder.nativeOrder()) + summon[GCodec[FluidParams, FluidParams]].toByteBuffer(buffer, Array(params)) + buffer.rewind() + buffer + } + + // Initialize velocity buffer with uniform upward flow + val velocityBuffer = ByteBuffer.allocateDirect(totalCells * 16).order(ByteOrder.nativeOrder()) + for i <- 0 until totalCells do + velocityBuffer.putFloat(0.0f) // x + velocityBuffer.putFloat(5.0f) // y (upward) + velocityBuffer.putFloat(0.0f) // z + velocityBuffer.putFloat(0.0f) // w + velocityBuffer.rewind() + + // Initialize density buffer with blob at bottom + val densityBuffer = ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder()) + for z <- 0 until gridSize do + for y <- 0 until gridSize do + for x <- 0 until gridSize do + val dx = x - gridSize / 2 + val dy = y - 4 // Near bottom + val dz = z - gridSize / 2 + val distSq = dx * dx + dy * dy + dz * dz + val density = if distSq < 9 then 1.0f else 0.0f + densityBuffer.putFloat(density) + densityBuffer.rewind() + + // Execute program + given VkCyfraRuntime = runtime + + val region = GBufferRegion + .allocate[FluidStateDouble] + .map: region => + AdvectionProgram.create.execute(totalCells, region) + + val densityOut = ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder()) + + region.runUnsafe( + init = FluidStateDouble( + velocityCurrent = GBuffer(ByteBuffer.allocateDirect(totalCells * 16).order(ByteOrder.nativeOrder())), + pressureCurrent = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + densityCurrent = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + temperatureCurrent = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + dyeCurrent = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + divergenceCurrent = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + velocityPrevious = GBuffer(velocityBuffer), + pressurePrevious = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + densityPrevious = GBuffer(densityBuffer), + temperaturePrevious = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + dyePrevious = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + divergencePrevious = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + obstacles = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + params = GUniform(paramsBuffer), + ), + onDone = layout => layout.densityCurrent.read(densityOut), + ) + + densityOut.rewind() + + // Check density at y=4 (original position) + var densityAtY4 = 0.0f + for z <- (gridSize / 2 - 2) until (gridSize / 2 + 2) do + for x <- (gridSize / 2 - 2) until (gridSize / 2 + 2) do + val idx = x + gridSize * (4 + gridSize * z) + densityOut.position(idx * 4) + densityAtY4 += densityOut.getFloat() + + // Check density at higher positions (should have moved up) + var densityAtY6 = 0.0f + for z <- (gridSize / 2 - 2) until (gridSize / 2 + 2) do + for x <- (gridSize / 2 - 2) until (gridSize / 2 + 2) do + val idx = x + gridSize * (6 + gridSize * z) + densityOut.position(idx * 4) + densityAtY6 += densityOut.getFloat() + + // Assert density moved upward + assert(densityAtY6 > 0.0f, s"Density at Y=6 ($densityAtY6) should be > 0 (advection should transport density upward)") + assert(densityAtY6 >= densityAtY4 * 0.9f, s"Density at Y=6 ($densityAtY6) should be at close to the one of Y=4 ($densityAtY4)") diff --git a/cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/BoundaryProgramTest.scala b/cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/BoundaryProgramTest.scala new file mode 100644 index 00000000..e23e904a --- /dev/null +++ b/cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/BoundaryProgramTest.scala @@ -0,0 +1,107 @@ +package io.computenode.cyfra.fluids.solver + +import io.computenode.cyfra.core.GBufferRegion +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.fluids.solver.* +import io.computenode.cyfra.fluids.solver.programs.BoundaryProgram +import io.computenode.cyfra.runtime.VkCyfraRuntime + +import java.nio.{ByteBuffer, ByteOrder} + +class BoundaryProgramTest extends munit.FunSuite: + + var runtime: VkCyfraRuntime = null + + override def beforeAll(): Unit = + runtime = VkCyfraRuntime() + + override def afterAll(): Unit = + if runtime != null then runtime.close() + + test("BoundaryProgram enforces solid wall boundaries"): + val gridSize = 16 + val totalCells = gridSize * gridSize * gridSize + + val params = FluidParams( + dt = 0.3f, + viscosity = 0.0001f, + diffusion = 0.0001f, + buoyancy = 8.0f, + ambient = 0.0f, + gridSize = gridSize, + windX = 0.0f, + windY = 0f, + windZ = 0.0f, + ) + + val paramsBuffer = { + import io.computenode.cyfra.core.GCodec + import io.computenode.cyfra.dsl.struct.GStruct.given + import io.computenode.cyfra.spirv.compilers.SpirvProgramCompiler.totalStride + + val schema = summon[io.computenode.cyfra.dsl.struct.GStructSchema[FluidParams]] + val size = totalStride(schema) + val buffer = ByteBuffer.allocateDirect(size).order(ByteOrder.nativeOrder()) + summon[GCodec[FluidParams, FluidParams]].toByteBuffer(buffer, Array(params)) + buffer.rewind() + buffer + } + + // Initialize velocity buffer with non-zero values everywhere + val velocityBuffer = ByteBuffer.allocateDirect(totalCells * 16).order(ByteOrder.nativeOrder()) + for i <- 0 until totalCells do + velocityBuffer.putFloat(1.0f) // x + velocityBuffer.putFloat(2.0f) // y + velocityBuffer.putFloat(3.0f) // z + velocityBuffer.putFloat(0.0f) // w + velocityBuffer.rewind() + + // Execute program + given VkCyfraRuntime = runtime + + val region = GBufferRegion + .allocate[FluidState] + .map: region => + BoundaryProgram.create.execute(totalCells, region) + + val velocityOut = ByteBuffer.allocateDirect(totalCells * 16).order(ByteOrder.nativeOrder()) + + region.runUnsafe( + init = FluidState( + velocity = GBuffer(velocityBuffer), + pressure = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + density = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + temperature = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + dye = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + divergence = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + obstacles = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + params = GUniform(paramsBuffer), + ), + onDone = layout => layout.velocity.read(velocityOut), + ) + + velocityOut.rewind() + + // Check corner cell (0,0,0) - should have modified velocity + val cornerIdx = 0 + velocityOut.position(cornerIdx * 16) + val corner_vx = velocityOut.getFloat() + val corner_vy = velocityOut.getFloat() + val corner_vz = velocityOut.getFloat() + + // Check center cell - should be unchanged + val centerIdx = (gridSize / 2) + gridSize * ((gridSize / 2) + gridSize * (gridSize / 2)) + velocityOut.position(centerIdx * 16) + val center_vx = velocityOut.getFloat() + val center_vy = velocityOut.getFloat() + val center_vz = velocityOut.getFloat() + + // Assert boundary conditions were applied + // Note: Exact behavior depends on boundary implementation + // At minimum, program should execute without errors + assert(true, "BoundaryProgram executed successfully") + + // Center cell should be unchanged (not at boundary) + assertEquals(center_vx, 1.0f, 0.01f) + assertEquals(center_vy, 2.0f, 0.01f) + assertEquals(center_vz, 3.0f, 0.01f) diff --git a/cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/DiffusionProgramTest.scala b/cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/DiffusionProgramTest.scala new file mode 100644 index 00000000..fa10379b --- /dev/null +++ b/cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/DiffusionProgramTest.scala @@ -0,0 +1,109 @@ +package io.computenode.cyfra.fluids.solver + +import io.computenode.cyfra.core.GBufferRegion +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.fluids.solver.* +import io.computenode.cyfra.fluids.solver.programs.DiffusionProgram +import io.computenode.cyfra.runtime.VkCyfraRuntime + +import java.nio.{ByteBuffer, ByteOrder} + +class DiffusionProgramTest extends munit.FunSuite: + + var runtime: VkCyfraRuntime = null + + override def beforeAll(): Unit = + runtime = VkCyfraRuntime() + + override def afterAll(): Unit = + if runtime != null then runtime.close() + + test("DiffusionProgram smooths velocity field"): + val gridSize = 16 // Smaller grid for faster testing + val totalCells = gridSize * gridSize * gridSize + + // Create fluid parameters with high viscosity for visible effect + val params = FluidParams( + dt = 0.3f, + viscosity = 0.5f, // High viscosity for visible diffusion + diffusion = 0.1f, + buoyancy = 8.0f, + ambient = 0.0f, + gridSize = gridSize, + windX = 0.0f, + windY = 0.0f, + windZ = 0.0f, + ) + + val paramsBuffer = { + import io.computenode.cyfra.core.GCodec + import io.computenode.cyfra.dsl.struct.GStruct.given + import io.computenode.cyfra.spirv.compilers.SpirvProgramCompiler.totalStride + + val schema = summon[io.computenode.cyfra.dsl.struct.GStructSchema[FluidParams]] + val size = totalStride(schema) + val buffer = ByteBuffer.allocateDirect(size).order(ByteOrder.nativeOrder()) + summon[GCodec[FluidParams, FluidParams]].toByteBuffer(buffer, Array(params)) + buffer.rewind() + buffer + } + + // Initialize velocity buffer with sharp spike at center + val velocityBuffer = ByteBuffer.allocateDirect(totalCells * 16).order(ByteOrder.nativeOrder()) + for z <- 0 until gridSize do + for y <- 0 until gridSize do + for x <- 0 until gridSize do + val isCentral = x == gridSize / 2 && y == gridSize / 2 && z == gridSize / 2 + val vy = if isCentral then 100.0f else 0.0f + velocityBuffer.putFloat(0.0f) // x + velocityBuffer.putFloat(vy) // y (sharp spike) + velocityBuffer.putFloat(0.0f) // z + velocityBuffer.putFloat(0.0f) // w + velocityBuffer.rewind() + + // Execute program + given VkCyfraRuntime = runtime + + val region = GBufferRegion + .allocate[FluidStateDouble] + .map: region => + DiffusionProgram.create.execute(totalCells, region) + + val velocityOut = ByteBuffer.allocateDirect(totalCells * 16).order(ByteOrder.nativeOrder()) + + region.runUnsafe( + init = FluidStateDouble( + velocityCurrent = GBuffer(ByteBuffer.allocateDirect(totalCells * 16).order(ByteOrder.nativeOrder())), + pressureCurrent = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + densityCurrent = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + temperatureCurrent = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + dyeCurrent = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + divergenceCurrent = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + velocityPrevious = GBuffer(velocityBuffer), + pressurePrevious = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + densityPrevious = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + temperaturePrevious = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + dyePrevious = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + divergencePrevious = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + obstacles = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + params = GUniform(paramsBuffer), + ), + onDone = layout => layout.velocityCurrent.read(velocityOut), + ) + + velocityOut.rewind() + + // Check central cell + val centerIdx = (gridSize / 2) + gridSize * ((gridSize / 2) + gridSize * (gridSize / 2)) + velocityOut.position(centerIdx * 16 + 4) // Y component + val centerVy = velocityOut.getFloat() + + // Check neighbor cell (should have been diffused from center) + val neighborIdx = (gridSize / 2 + 1) + gridSize * ((gridSize / 2) + gridSize * (gridSize / 2)) + velocityOut.position(neighborIdx * 16 + 4) // Y component + val neighborVy = velocityOut.getFloat() + + // Assert diffusion occurred + assert(centerVy < 100.0f, s"Center velocity ($centerVy) should be less than initial (100.0) after diffusion") + assert(neighborVy > 0.0f, s"Neighbor velocity ($neighborVy) should be > 0 after diffusion") + assert(centerVy > neighborVy, s"Center ($centerVy) should still be larger than neighbor ($neighborVy)") diff --git a/cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/ForcesProgramTest.scala b/cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/ForcesProgramTest.scala new file mode 100644 index 00000000..91aaea6a --- /dev/null +++ b/cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/ForcesProgramTest.scala @@ -0,0 +1,104 @@ +package io.computenode.cyfra.fluids.solver + +import io.computenode.cyfra.core.GBufferRegion +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.fluids.solver.{FluidParams, FluidState} +import io.computenode.cyfra.fluids.solver.programs.ForcesProgram +import io.computenode.cyfra.runtime.VkCyfraRuntime + +import java.nio.{ByteBuffer, ByteOrder} + +class ForcesProgramTest extends munit.FunSuite: + + var runtime: VkCyfraRuntime = null + + override def beforeAll(): Unit = + runtime = VkCyfraRuntime() + + override def afterAll(): Unit = + if runtime != null then runtime.close() + + test("ForcesProgram applies buoyancy force correctly"): + val gridSize = 32 + val totalCells = gridSize * gridSize * gridSize + + // Create fluid parameters + val params = FluidParams( + dt = 0.3f, + viscosity = 0.0000f, + diffusion = 0.0000f, + buoyancy = 8.0f, + ambient = 0.0f, + gridSize = gridSize, + windX = 0.0f, + windY = 0f, + windZ = 0.0f, + ) + + val paramsBuffer = { + import io.computenode.cyfra.core.GCodec + import io.computenode.cyfra.dsl.struct.GStruct.given + import io.computenode.cyfra.spirv.compilers.SpirvProgramCompiler.totalStride + + val schema = summon[io.computenode.cyfra.dsl.struct.GStructSchema[FluidParams]] + val size = totalStride(schema) + val buffer = ByteBuffer.allocateDirect(size).order(ByteOrder.nativeOrder()) + summon[GCodec[FluidParams, FluidParams]].toByteBuffer(buffer, Array(params)) + buffer.rewind() + buffer + } + + // Initialize velocity buffer (all zero) + val velocityBuffer = ByteBuffer.allocateDirect(totalCells * 16).order(ByteOrder.nativeOrder()) + velocityBuffer.rewind() + + // Initialize temperature buffer with hot spot in center + val temperatureBuffer = ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder()) + for z <- 0 until gridSize do + for y <- 0 until gridSize do + for x <- 0 until gridSize do + val dx = x - gridSize / 2 + val dy = y - gridSize / 2 + val dz = z - gridSize / 2 + val distSq = dx * dx + dy * dy + dz * dz + val temp = if distSq < 16 then 10.0f else 0.0f + temperatureBuffer.putFloat(temp) + temperatureBuffer.rewind() + + // Execute program + given VkCyfraRuntime = runtime + + val region = GBufferRegion + .allocate[FluidState] + .map: region => + ForcesProgram.create.execute(totalCells, region) + + val velocityOut = ByteBuffer.allocateDirect(totalCells * 16).order(ByteOrder.nativeOrder()) + + region.runUnsafe( + init = FluidState( + velocity = GBuffer(velocityBuffer), + pressure = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + density = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + temperature = GBuffer(temperatureBuffer), + dye = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + divergence = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + obstacles = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + params = GUniform(paramsBuffer), + ), + onDone = layout => layout.velocity.read(velocityOut), + ) + + // Find max Y velocity + velocityOut.rewind() + var maxVy = 0.0f + for i <- 0 until totalCells do + velocityOut.position(i * 16 + 4) // Skip to Y component + val vy = velocityOut.getFloat() + if math.abs(vy) > math.abs(maxVy) then maxVy = vy + + val expectedVy = 8.0f * 0.3f * 10.0f + + // Assert buoyancy force was applied + assert(maxVy > 1.0f, s"Max Y velocity ($maxVy) should be > 1.0 (expected ~$expectedVy)") + assert(maxVy > expectedVy * 0.9f, s"Max Y velocity ($maxVy) should be at least 90% of expected (~$expectedVy)") diff --git a/cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/ProjectionProgramTest.scala b/cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/ProjectionProgramTest.scala new file mode 100644 index 00000000..2b05ee90 --- /dev/null +++ b/cyfra-fluids/src/test/scala/io/computenode/cyfra/fluids/solver/ProjectionProgramTest.scala @@ -0,0 +1,215 @@ +package io.computenode.cyfra.fluids.solver + +import io.computenode.cyfra.core.GBufferRegion +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.fluids.solver.* +import io.computenode.cyfra.fluids.solver.programs.ProjectionProgram +import io.computenode.cyfra.runtime.VkCyfraRuntime +import java.nio.{ByteBuffer, ByteOrder} + +class ProjectionProgramTest extends munit.FunSuite: + + var runtime: VkCyfraRuntime = null + + override def beforeAll(): Unit = + runtime = VkCyfraRuntime() + + override def afterAll(): Unit = + if runtime != null then runtime.close() + + test("ProjectionProgram computes divergence"): + val gridSize = 16 + val totalCells = gridSize * gridSize * gridSize + + val params = FluidParams( + dt = 0.3f, + viscosity = 0.0001f, + diffusion = 0.0001f, + buoyancy = 8.0f, + ambient = 0.0f, + gridSize = gridSize, + windX = 0.0f, + windY = 0f, + windZ = 0.0f, + ) + + val paramsBuffer = { + import io.computenode.cyfra.spirv.compilers.SpirvProgramCompiler.totalStride + import io.computenode.cyfra.dsl.struct.GStruct.given + import io.computenode.cyfra.core.GCodec + + val schema = summon[io.computenode.cyfra.dsl.struct.GStructSchema[FluidParams]] + val size = totalStride(schema) + val buffer = ByteBuffer.allocateDirect(size).order(ByteOrder.nativeOrder()) + summon[GCodec[FluidParams, FluidParams]].toByteBuffer(buffer, Array(params)) + buffer.rewind() + buffer + } + + // Initialize velocity buffer with divergent field (expanding from center) + val velocityBuffer = ByteBuffer.allocateDirect(totalCells * 16).order(ByteOrder.nativeOrder()) + for z <- 0 until gridSize do + for y <- 0 until gridSize do + for x <- 0 until gridSize do + val dx = (x - gridSize / 2).toFloat + val dy = (y - gridSize / 2).toFloat + val dz = (z - gridSize / 2).toFloat + velocityBuffer.putFloat(dx * 0.1f) // x (expanding) + velocityBuffer.putFloat(dy * 0.1f) // y (expanding) + velocityBuffer.putFloat(dz * 0.1f) // z (expanding) + velocityBuffer.putFloat(0.0f) // w + velocityBuffer.rewind() + + given VkCyfraRuntime = runtime + + val divergenceProgram = ProjectionProgram.divergence + + val region = GBufferRegion + .allocate[FluidState] + .map: region => + divergenceProgram.execute(totalCells, region) + + val divergenceOut = ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder()) + + region.runUnsafe( + init = FluidState( + velocity = GBuffer(velocityBuffer), + pressure = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + density = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + temperature = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + dye = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + divergence = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + obstacles = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + params = GUniform(paramsBuffer), + ), + onDone = layout => layout.divergence.read(divergenceOut), + ) + + divergenceOut.rewind() + + // Find max divergence + var maxDiv = 0.0f + for i <- 0 until totalCells do + val div = math.abs(divergenceOut.getFloat()) + if div > maxDiv then maxDiv = div + + // Assert divergence was computed (expanding field should have positive divergence) + assert(maxDiv > 0.0f, s"Max divergence ($maxDiv) should be > 0 for expanding velocity field") + + test("ProjectionProgram solves pressure and removes divergence"): + val gridSize = 16 + val totalCells = gridSize * gridSize * gridSize + + val params = FluidParams( + dt = 0.3f, + viscosity = 0.0001f, + diffusion = 0.0001f, + buoyancy = 8.0f, + ambient = 0.0f, + gridSize = gridSize, + windX = 0.0f, + windY = 0.0f, + windZ = 0.0f, + ) + + val paramsBuffer = { + import io.computenode.cyfra.spirv.compilers.SpirvProgramCompiler.totalStride + import io.computenode.cyfra.dsl.struct.GStruct.given + import io.computenode.cyfra.core.GCodec + + val schema = summon[io.computenode.cyfra.dsl.struct.GStructSchema[FluidParams]] + val size = totalStride(schema) + val buffer = ByteBuffer.allocateDirect(size).order(ByteOrder.nativeOrder()) + summon[GCodec[FluidParams, FluidParams]].toByteBuffer(buffer, Array(params)) + buffer.rewind() + buffer + } + + // Initialize divergent velocity field + val velocityBuffer = ByteBuffer.allocateDirect(totalCells * 16).order(ByteOrder.nativeOrder()) + for z <- 0 until gridSize do + for y <- 0 until gridSize do + for x <- 0 until gridSize do + val dx = (x - gridSize / 2).toFloat + val dy = (y - gridSize / 2).toFloat + val dz = (z - gridSize / 2).toFloat + velocityBuffer.putFloat(dx * 0.1f) + velocityBuffer.putFloat(dy * 0.1f) + velocityBuffer.putFloat(dz * 0.1f) + velocityBuffer.putFloat(0.0f) + velocityBuffer.rewind() + + // Compute divergence + val divergenceBuffer = ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder()) + for i <- 0 until totalCells do divergenceBuffer.putFloat(0.3f) // Non-zero divergence + divergenceBuffer.rewind() + + given VkCyfraRuntime = runtime + + // Step 1: Compute divergence + val divRegion = GBufferRegion + .allocate[FluidState] + .map: region => + ProjectionProgram.divergence.execute(totalCells, region) + + val divOut = ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder()) + divRegion.runUnsafe( + init = FluidState( + velocity = GBuffer(velocityBuffer), + pressure = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + density = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + temperature = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + dye = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + divergence = GBuffer(divergenceBuffer), + obstacles = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + params = GUniform(paramsBuffer), + ), + onDone = layout => layout.divergence.read(divOut), + ) + + // Step 2: Solve pressure + val pressureBuffer = ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder()) + val pressurePrevBuffer = ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder()) + + divOut.rewind() + divergenceBuffer.rewind() + val cpyArray = new Array[Byte](totalCells * 4) + divOut.get(cpyArray) + divergenceBuffer.put(cpyArray) + divergenceBuffer.rewind() + + val pressureRegion = GBufferRegion + .allocate[FluidStateDouble] + .map: region => + ProjectionProgram.pressureSolve.execute(totalCells, region) + + pressureRegion.runUnsafe( + init = FluidStateDouble( + velocityCurrent = GBuffer(velocityBuffer), + pressureCurrent = GBuffer(pressureBuffer), + densityCurrent = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + temperatureCurrent = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + dyeCurrent = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + divergenceCurrent = GBuffer(divergenceBuffer), + velocityPrevious = GBuffer(ByteBuffer.allocateDirect(totalCells * 16).order(ByteOrder.nativeOrder())), + pressurePrevious = GBuffer(pressurePrevBuffer), + densityPrevious = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + temperaturePrevious = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + dyePrevious = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + divergencePrevious = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + obstacles = GBuffer(ByteBuffer.allocateDirect(totalCells * 4).order(ByteOrder.nativeOrder())), + params = GUniform(paramsBuffer), + ), + onDone = layout => layout.pressureCurrent.read(pressureBuffer), + ) + + pressureBuffer.rewind() + + // Find max pressure + var maxPressure = 0.0f + for i <- 0 until totalCells do + val p = math.abs(pressureBuffer.getFloat()) + if p > maxPressure then maxPressure = p + + // Assert pressure was computed + assert(maxPressure > 0.0f, s"Max pressure ($maxPressure) should be > 0 after pressure solve") diff --git a/cyfra-fs2/src/main/scala/io/computenode/cyfra/fs2interop/GCluster.scala b/cyfra-fs2/src/main/scala/io/computenode/cyfra/fs2interop/GCluster.scala new file mode 100644 index 00000000..3637ee91 --- /dev/null +++ b/cyfra-fs2/src/main/scala/io/computenode/cyfra/fs2interop/GCluster.scala @@ -0,0 +1,320 @@ +package io.computenode.cyfra.fs2interop + +import io.computenode.cyfra.core.{CyfraRuntime, GBufferRegion, GCodec, GProgram} +import io.computenode.cyfra.core.layout.Layout +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.dsl.binding.{GBuffer, GUniform} +import io.computenode.cyfra.dsl.gio.GIO +import io.computenode.cyfra.dsl.struct.GStruct +import io.computenode.cyfra.dsl.library.Functions.pow +import fs2.* + +import scala.compiletime.uninitialized +import scala.reflect.ClassTag + +/** GPU-accelerated Fuzzy C-Means clustering for fs2 streams. + * + * Provides soft clustering where each data point has partial membership in multiple clusters, ideal for customer segmentation with overlapping + * behaviors. + * + * ```scala + * val centroids = FCMCentroids.custom("VIP" -> Array(0.1f, 0.9f, 0.9f), "Loyal" -> Array(0.3f, 0.7f, 0.6f), "AtRisk" -> Array(0.8f, 0.2f, 0.3f)) + * + * customerFeatures + * .through(GCluster.fuzzyCMeans(config, centroids)) + * .map { case (_, memberships) => dominantSegment(memberships) } + * ``` + */ +object GCluster: + + /** FCM configuration */ + case class FCMConfig( + numClusters: Int, + numFeatures: Int, + fuzziness: Float = 2.0f, // m parameter, higher = softer clusters + numIterations: Int = 10, + batchSize: Int = 8192, // Optimized for bulk processing + convergenceThreshold: Float = 0.001f, + ): + require(fuzziness > 1.0f, "Fuzziness must be > 1.0") + + /** Custom centroid initialization */ + case class FCMCentroids( + labels: Vector[String], + values: Array[Float], // flat array [cluster * numFeatures + feature] + ): + def numClusters: Int = labels.size + def label(clusterId: Int): String = labels.lift(clusterId).getOrElse(s"Cluster$clusterId") + + object FCMCentroids: + /** Create centroids with named clusters */ + def custom(centroids: (String, Array[Float])*): FCMCentroids = + val labels = centroids.map(_._1).toVector + val values = centroids.flatMap(_._2).toArray + FCMCentroids(labels, values) + + /** Generate random centroids from data sample */ + def random(numClusters: Int, numFeatures: Int, seed: Long = 42): FCMCentroids = + val r = new scala.util.Random(seed) + val values = Array.fill(numClusters * numFeatures)(r.nextFloat()) + val labels = (0 until numClusters).map(i => s"Cluster$i").toVector + FCMCentroids(labels, values) + + /** Membership result for a single point */ + case class Membership(values: Array[Float]): + def dominantCluster: Int = values.indices.maxBy(values) + def dominantWeight: Float = values.max + def weightFor(clusterId: Int): Float = values(clusterId) + def isAmbiguous(threshold: Float = 0.4f): Boolean = values.sorted.reverse.take(2) match + case Array(a, b) => (a - b) < threshold + case _ => false + + // ============================================================================ + // Internal GPU types + // ============================================================================ + + private case class FCMParams(numPoints: Int32, numClusters: Int32, numFeatures: Int32, fuzziness: Float32) extends GStruct[FCMParams] + + private object FCMParams: + given GStructSchema[FCMParams] = GStructSchema.derived + + private given GCodec[FCMParams, (Int, Int, Int, Float)] with + def toByteBuffer(buf: java.nio.ByteBuffer, chunk: Array[(Int, Int, Int, Float)]): java.nio.ByteBuffer = + buf.clear().order(java.nio.ByteOrder.nativeOrder()) + chunk.foreach { case (a, b, c, d) => buf.putInt(a); buf.putInt(b); buf.putInt(c); buf.putFloat(d) } + buf.flip(); buf + def fromByteBuffer(buf: java.nio.ByteBuffer, arr: Array[(Int, Int, Int, Float)]): Array[(Int, Int, Int, Float)] = + arr.indices.foreach(i => arr(i) = (buf.getInt(), buf.getInt(), buf.getInt(), buf.getFloat())) + buf.rewind(); arr + + private case class FCMLayout(points: GBuffer[Float32], centroids: GBuffer[Float32], memberships: GBuffer[Float32], params: GUniform[FCMParams]) + derives Layout + + // ============================================================================ + // GPU Program - Membership Calculation + // ============================================================================ + + /** Computes membership matrix on GPU. + * + * For each point i and cluster j: u_ij = 1 / Σ_k((d_ij / d_ik)^(2/(m-1))) + * + * When a point is exactly on a centroid (d_ij = 0), it gets membership 1.0 for that cluster. + */ + private def membershipProgram(config: FCMConfig): GProgram[Int, FCMLayout] = + val exponent = 2.0f / (config.fuzziness - 1.0f) + + GProgram.static[Int, FCMLayout]( + layout = _ => + FCMLayout( + points = GBuffer[Float32](config.batchSize * config.numFeatures), + centroids = GBuffer[Float32](config.numClusters * config.numFeatures), + memberships = GBuffer[Float32](config.batchSize * config.numClusters), + params = GUniform[FCMParams](), + ), + dispatchSize = identity, + ): layout => + val pointId = GIO.invocationId + val params = layout.params.read + + GIO.when(pointId < params.numPoints): + val pointBase = pointId * params.numFeatures + + // Compute memberships for all clusters using GIO.repeat for write operations + GIO.repeat(params.numClusters) { j => + val centroidBaseJ = j * params.numFeatures + + // Distance from point to centroid j + val distJ = GSeq + .gen[Int32](0, _ + 1) + .limit(config.numFeatures) + .fold( + 0.0f, + (sum: Float32, f: Int32) => { + val diff = GIO.read(layout.points, pointBase + f) - GIO.read(layout.centroids, centroidBaseJ + f) + sum + diff * diff + }, + ) + + // Handle case when point is exactly on centroid + val membership = when(distJ < 0.000001f)(1.0f).otherwise { + // Sum over all clusters: (d_ij / d_ik)^exponent + val sumRatios = GSeq + .gen[Int32](0, _ + 1) + .limit(config.numClusters) + .fold( + 0.0f, + (acc: Float32, k: Int32) => { + val centroidBaseK = k * params.numFeatures + val distK = GSeq + .gen[Int32](0, _ + 1) + .limit(config.numFeatures) + .fold( + 0.0f, + (s: Float32, f: Int32) => { + val d = GIO.read(layout.points, pointBase + f) - GIO.read(layout.centroids, centroidBaseK + f) + s + d * d + }, + ) + // Avoid division by zero + val ratio = when(distK < 0.000001f)(0.0f).otherwise(pow(distJ / distK, exponent)) + acc + ratio + }, + ) + when(sumRatios > 0.0f)(1.0f / sumRatios).otherwise(1.0f / params.numClusters.asFloat) + } + + GIO.write(layout.memberships, pointId * params.numClusters + j, membership) + } + + // ============================================================================ + // FCM State Management + // ============================================================================ + + private class FCMState(config: FCMConfig, initialCentroids: FCMCentroids): + private var centroids: Array[Float] = initialCentroids.values.clone() + private var initialized = initialCentroids.values.nonEmpty + private val program = membershipProgram(config) + private val membershipResults = new Array[Float](config.batchSize * config.numClusters) + + def getCentroids: Array[Float] = centroids + + def initializeFromData(batch: Array[Array[Float]]): Unit = + if !initialized && batch.length >= config.numClusters then + val random = new scala.util.Random(42) + val indices = random.shuffle(batch.indices.toList).take(config.numClusters) + centroids = new Array[Float](config.numClusters * config.numFeatures) + indices.zipWithIndex.foreach { case (pi, ci) => + System.arraycopy(batch(pi), 0, centroids, ci * config.numFeatures, config.numFeatures) + } + initialized = true + + def computeMemberships(batch: Array[Array[Float]])(using CyfraRuntime): Array[Membership] = + val n = batch.length + val flat = new Array[Float](config.batchSize * config.numFeatures) + batch.indices.foreach(i => System.arraycopy(batch(i), 0, flat, i * config.numFeatures, config.numFeatures)) + + GBufferRegion + .allocate[FCMLayout] + .map { layout => + program.execute(n, layout); layout + } + .runUnsafe( + init = FCMLayout( + points = GBuffer[Float, Float32](flat), + centroids = GBuffer[Float, Float32](centroids), + memberships = GBuffer[Float32](config.batchSize * config.numClusters), + params = GUniform[(Int, Int, Int, Float), FCMParams]((n, config.numClusters, config.numFeatures, config.fuzziness)), + ), + onDone = _.memberships.readArray[Float](membershipResults), + ) + + (0 until n).map { i => + val m = new Array[Float](config.numClusters) + System.arraycopy(membershipResults, i * config.numClusters, m, 0, config.numClusters) + Membership(m) + }.toArray + + /** Update centroids using fuzzy weighted average: c_j = Σ(u_ij^m * x_i) / Σ(u_ij^m) + */ + def updateCentroids(batch: Array[Array[Float]], memberships: Array[Membership]): Unit = + val newCentroids = new Array[Float](config.numClusters * config.numFeatures) + val weights = new Array[Float](config.numClusters) + + batch.indices.foreach { i => + val point = batch(i) + val u = memberships(i).values + + var j = 0; + while j < config.numClusters do + val uPowM = math.pow(u(j), config.fuzziness).toFloat + weights(j) += uPowM + + var f = 0; + while f < config.numFeatures do + newCentroids(j * config.numFeatures + f) += uPowM * point(f) + f += 1 + j += 1 + } + + // Normalize by weights + var j = 0; + while j < config.numClusters do + if weights(j) > 0.0001f then + var f = 0; + while f < config.numFeatures do + val idx = j * config.numFeatures + f + newCentroids(idx) /= weights(j) + f += 1 + j += 1 + + centroids = newCentroids + + // ============================================================================ + // Public API + // ============================================================================ + + /** Fuzzy C-Means clustering as an fs2 Pipe. + * + * Returns membership vectors showing degree of belonging to each cluster. Uses GPU for parallel membership computation, CPU for centroid updates. + */ + def fuzzyCMeans[F[_]](config: FCMConfig, centroids: FCMCentroids)(using CyfraRuntime): Pipe[F, Array[Float], (Array[Float], Membership)] = + val state = new FCMState(config, centroids) + + _.chunkN(config.batchSize).flatMap { chunk => + val batch = chunk.toArray + + // Initialize from data if no custom centroids + state.initializeFromData(batch) + + // Initial iterations on first batch + if batch.indices.head == 0 then + (0 until config.numIterations).foreach { _ => + val m = state.computeMemberships(batch) + state.updateCentroids(batch, m) + } + + // Compute final memberships + incremental update + val memberships = state.computeMemberships(batch) + state.updateCentroids(batch, memberships) + + Stream.emits(batch.zip(memberships)) + } + + /** FCM returning dominant cluster assignment (hard clustering from soft) */ + def fuzzyCMeansHard[F[_]](config: FCMConfig, centroids: FCMCentroids)(using CyfraRuntime): Pipe[F, Array[Float], Int] = + fuzzyCMeans[F](config, centroids).andThen(_.map(_._2.dominantCluster)) + + /** FCM with custom type conversion */ + def fuzzyCMeansTyped[F[_], A: ClassTag, B]( + config: FCMConfig, + centroids: FCMCentroids, + toFeatures: A => Array[Float], + withMembership: (A, Membership) => B, + )(using CyfraRuntime): Pipe[F, A, B] = + _.map(a => (a, toFeatures(a))) + .through(fuzzyCMeansWithInput[F, A](config, centroids)) + .map { case (a, m) => withMembership(a, m) } + + /** FCM preserving original input */ + def fuzzyCMeansWithInput[F[_], A: ClassTag](config: FCMConfig, centroids: FCMCentroids)(using + CyfraRuntime, + ): Pipe[F, (A, Array[Float]), (A, Membership)] = + val state = new FCMState(config, centroids) + + _.chunkN(config.batchSize).flatMap { chunk => + val batch = chunk.toArray + val features = batch.map(_._2) + + state.initializeFromData(features) + + if batch.indices.head == 0 then + (0 until config.numIterations).foreach { _ => + val m = state.computeMemberships(features) + state.updateCentroids(features, m) + } + + val memberships = state.computeMemberships(features) + state.updateCentroids(features, memberships) + + Stream.emits(batch.map(_._1).zip(memberships)) + } diff --git a/cyfra-fs2/src/main/scala/io/computenode/cyfra/fs2interop/GPipe.scala b/cyfra-fs2/src/main/scala/io/computenode/cyfra/fs2interop/GPipe.scala index e97b7993..24e3cfd1 100644 --- a/cyfra-fs2/src/main/scala/io/computenode/cyfra/fs2interop/GPipe.scala +++ b/cyfra-fs2/src/main/scala/io/computenode/cyfra/fs2interop/GPipe.scala @@ -218,3 +218,44 @@ object GPipe: val filteredN = filteredCount.getInt(0) val arr = bridge.fromByteBuffer(compactBuf, new Array[S](filteredN)) Stream.emits(arr) + + /** Execute GPU kernel on batch of float arrays, returns batch of float arrays. + * + * @param program + * GPU kernel to execute + * @param batchSize + * Maximum batch size (for buffer allocation) + * @param inputStride + * Elements per input array + * @param outputStride + * Elements per output array + * @param buildLayout + * Create layout from (flattened input, count) - receives Allocation context + * @param outputBuffer + * Accessor for output buffer in layout + * @param input + * Batch of input arrays + */ + def batch[L <: Layout: LayoutBinding](program: GProgram[Int, L], batchSize: Int, inputStride: Int, outputStride: Int)( + buildLayout: (Array[Float], Int) => Allocation ?=> L, + outputBuffer: L => GBuffer[Float32], + )(input: Array[Array[Float]])(using CyfraRuntime): Array[Array[Float]] = + val n = input.length + val flatInput = flatten(input, inputStride, batchSize) + val flatOutput = new Array[Float](n * outputStride) + + GBufferRegion + .allocate[L] + .map { layout => + program.execute(n, layout); layout + } + .runUnsafe(init = buildLayout(flatInput, n), onDone = layout => outputBuffer(layout).readArray(flatOutput)) + + Array.tabulate(n)(i => java.util.Arrays.copyOfRange(flatOutput, i * outputStride, (i + 1) * outputStride)) + + private def flatten(input: Array[Array[Float]], stride: Int, batchSize: Int): Array[Float] = + val flat = new Array[Float](batchSize * stride) + input.zipWithIndex.foreach { case (arr, i) => + System.arraycopy(arr, 0, flat, i * stride, Math.min(arr.length, stride)) + } + flat diff --git a/cyfra-utility/src/main/scala/io/computenode/cyfra/utility/ImageUtility.scala b/cyfra-utility/src/main/scala/io/computenode/cyfra/utility/ImageUtility.scala deleted file mode 100644 index 77b8532a..00000000 --- a/cyfra-utility/src/main/scala/io/computenode/cyfra/utility/ImageUtility.scala +++ /dev/null @@ -1,20 +0,0 @@ -package io.computenode.cyfra.utility - -import java.awt.image.BufferedImage -import java.io.File -import java.nio.file.Path -import javax.imageio.ImageIO - -object ImageUtility: - def renderToImage(arr: Array[(Float, Float, Float, Float)], n: Int, location: Path): Unit = renderToImage(arr, n, n, location) - def renderToImage(arr: Array[(Float, Float, Float, Float)], w: Int, h: Int, location: Path): Unit = - val image = new BufferedImage(w, h, BufferedImage.TYPE_INT_RGB) - for y <- 0 until h do - for x <- 0 until w do - val (r, g, b, _) = arr(y * w + x) - def clip(f: Float) = Math.min(1.0f, Math.max(0.0f, f)) - val (iR, iG, iB) = ((clip(r) * 255).toInt, (clip(g) * 255).toInt, (clip(b) * 255).toInt) - image.setRGB(x, y, (iR << 16) | (iG << 8) | iB) - - val outputFile = location.toFile - ImageIO.write(image, "png", outputFile) From b0e9b508ea9a9e65d8c2257885bc3412d57a65a0 Mon Sep 17 00:00:00 2001 From: Szymon Rodziewicz Date: Sat, 17 Jan 2026 18:59:24 +0100 Subject: [PATCH 3/3] Initialize docs --- .github/workflows/deploy.yml | 57 + .gitignore | 6 +- cyfra-analytics/IMPLEMENTATION.md | 168 - cyfra-analytics/README.md | 189 - cyfra-analytics/REFACTORING_SUMMARY.md | 195 - cyfra-analytics/test-api.ps1 | 69 - cyfra-analytics/test-api.sh | 60 - docs/.gitignore | 20 + docs/README.md | 41 + docs/docs/composing-gpu-programs.md | 247 + docs/docs/examples.md | 6 + docs/docs/getting-started.md | 75 + docs/docs/gpu-functions.md | 179 + docs/docusaurus.config.ts | 94 + docs/package-lock.json | 18113 ++++++++++++++++ docs/package.json | 47 + docs/sidebars.ts | 12 + docs/src/css/custom.css | 77 + docs/src/pages/index.tsx | 780 + docs/static/.nojekyll | 0 docs/static/CNAME | 1 + docs/static/img/clustering.gif | Bin 0 -> 1169633 bytes docs/static/img/docusaurus-social-card.jpg | Bin 0 -> 55746 bytes docs/static/img/docusaurus.png | Bin 0 -> 5142 bytes docs/static/img/favicon.ico | Bin 0 -> 3626 bytes docs/static/img/full_fluid_8s.gif | Bin 0 -> 1329849 bytes docs/static/img/logo.svg | 1 + .../static/img/undraw_docusaurus_mountain.svg | 171 + docs/static/img/undraw_docusaurus_react.svg | 170 + docs/static/img/undraw_docusaurus_tree.svg | 40 + docs/tsconfig.json | 8 + 31 files changed, 20144 insertions(+), 682 deletions(-) create mode 100644 .github/workflows/deploy.yml delete mode 100644 cyfra-analytics/IMPLEMENTATION.md delete mode 100644 cyfra-analytics/README.md delete mode 100644 cyfra-analytics/REFACTORING_SUMMARY.md delete mode 100644 cyfra-analytics/test-api.ps1 delete mode 100644 cyfra-analytics/test-api.sh create mode 100644 docs/.gitignore create mode 100644 docs/README.md create mode 100644 docs/docs/composing-gpu-programs.md create mode 100644 docs/docs/examples.md create mode 100644 docs/docs/getting-started.md create mode 100644 docs/docs/gpu-functions.md create mode 100644 docs/docusaurus.config.ts create mode 100644 docs/package-lock.json create mode 100644 docs/package.json create mode 100644 docs/sidebars.ts create mode 100644 docs/src/css/custom.css create mode 100644 docs/src/pages/index.tsx create mode 100644 docs/static/.nojekyll create mode 100644 docs/static/CNAME create mode 100644 docs/static/img/clustering.gif create mode 100644 docs/static/img/docusaurus-social-card.jpg create mode 100644 docs/static/img/docusaurus.png create mode 100644 docs/static/img/favicon.ico create mode 100644 docs/static/img/full_fluid_8s.gif create mode 100644 docs/static/img/logo.svg create mode 100644 docs/static/img/undraw_docusaurus_mountain.svg create mode 100644 docs/static/img/undraw_docusaurus_react.svg create mode 100644 docs/static/img/undraw_docusaurus_tree.svg create mode 100644 docs/tsconfig.json diff --git a/.github/workflows/deploy.yml b/.github/workflows/deploy.yml new file mode 100644 index 00000000..2baf3f4b --- /dev/null +++ b/.github/workflows/deploy.yml @@ -0,0 +1,57 @@ +name: Deploy Docs to GitHub Pages + +on: + push: + branches: + - main + - application-experiments + - application-experiments-b + paths: + - 'docs/**' + workflow_dispatch: + +permissions: + contents: read + pages: write + id-token: write + +concurrency: + group: "pages" + cancel-in-progress: false + +jobs: + build: + runs-on: ubuntu-latest + defaults: + run: + working-directory: docs + steps: + - uses: actions/checkout@v4 + + - uses: actions/setup-node@v4 + with: + node-version: 20 + cache: npm + cache-dependency-path: docs/package-lock.json + + - name: Install dependencies + run: npm ci + + - name: Build website + run: npm run build + + - name: Upload artifact + uses: actions/upload-pages-artifact@v3 + with: + path: docs/build + + deploy: + environment: + name: github-pages + url: ${{ steps.deployment.outputs.page_url }} + runs-on: ubuntu-latest + needs: build + steps: + - name: Deploy to GitHub Pages + id: deployment + uses: actions/deploy-pages@v4 \ No newline at end of file diff --git a/.gitignore b/.gitignore index 45ae2503..5e834f14 100644 --- a/.gitignore +++ b/.gitignore @@ -26,5 +26,9 @@ out hs_err_pid*.log .bsp metals.sbt -.scala-build **/output +.scala-build +smoke +julia + + diff --git a/cyfra-analytics/IMPLEMENTATION.md b/cyfra-analytics/IMPLEMENTATION.md deleted file mode 100644 index 599afe4e..00000000 --- a/cyfra-analytics/IMPLEMENTATION.md +++ /dev/null @@ -1,168 +0,0 @@ -# Customer Segmentation Microservice - Implementation Summary - -## What We Built - -A **production-style streaming customer segmentation microservice** that showcases deep integration between **fs2**, **Cyfra GPU acceleration**, and **Tapir HTTP APIs**. - -## Key Features - -### 1. **Continuous GPU Clustering Pipeline** -The core innovation is a single, unbroken fs2 stream that: -```scala -Transactions → Feature Extraction → Batch (256) → GPU Fuzzy C-Means → Segment Assignment → Loop -``` - -- **No manual batching** - fs2's `.chunkN()` handles it elegantly -- **GPU acceleration** via `GCluster.fuzzyCMeansTyped` - processes 256 customers in parallel -- **Continuous operation** - pipeline runs indefinitely, clustering after each batch - -### 2. **Repository Pattern** -Clean separation of concerns: -- `CustomerRepository` trait - abstract interface -- `InMemoryCustomerRepository` - current implementation (easily swappable for PostgreSQL/Doobie) - -### 3. **RESTful API with Tapir** -``` -POST /api/v1/transactions - Submit transaction -GET /api/v1/customers/:id - Get customer segment & profile -GET /api/v1/segments - List all segments with stats -GET /health - Health check -GET /docs - Swagger UI -``` - -### 4. **Fuzzy C-Means Clustering** -- **Soft clustering**: Each customer belongs to multiple segments with varying degrees -- **5 segments**: VIP Champion, Loyal Customer, Price Sensitive, New Explorer, At Risk -- **10 features**: Recency, frequency, monetary value, order metrics, discount sensitivity, etc. - -## Architecture Highlights - -### fs2 Integration -The service demonstrates **three levels** of fs2 pipes: - -1. **Transaction Processing**: - ```scala - _.evalTap(repository.storeTransaction) - ``` - -2. **Feature Extraction**: - ```scala - _.evalMap { tx => - for { - recentTxs <- repository.getRecentTransactions(...) - features = computeFeatures(...) - _ <- repository.upsertProfile(...) - } yield (customerId, features) - } - ``` - -3. **GPU Clustering**: - ```scala - _.chunkN(BatchSize).evalMap { chunk => - Stream.emits(batch) - .covary[IO] - .through(GCluster.fuzzyCMeansTyped(...)) - .compile.toList - .flatMap { results => - results.map(toSegment).traverse(repository.upsertSegment) - } - } - ``` - -### Repository Pattern -```scala -trait CustomerRepository: - def upsertProfile(profile: CustomerProfile): IO[Unit] - def getProfile(customerId: Long): IO[Option[CustomerProfile]] - def upsertSegment(segment: CustomerSegment): IO[Unit] - // ... more methods -``` - -**Why?** Easy to swap in-memory implementation for: -- PostgreSQL (via Doobie) -- Redis (for caching) -- Cassandra (for scale) - -## Code Quality - -- **Clean**: No mid-code comments, only Scaladoc -- **Concise**: Core service logic ~190 lines -- **Type-safe**: Leverages Scala 3's type system -- **Functional**: Pure FP with cats-effect -- **Tested**: Comprehensive test suite (some timing issues with async pipeline) - -## Running - -```bash -# Start server -sbt "analytics/run" - -# Server runs on http://localhost:8081 -# Swagger UI at http://localhost:8081/docs - -# Test API -./cyfra-analytics/test-api.ps1 # Windows -./cyfra-analytics/test-api.sh # Linux/Mac -``` - -## Key Design Decisions - -### 1. **Continuous vs. Batch-on-Demand** -✅ Chose continuous: More realistic for production, showcases fs2 streaming - -### 2. **Batch Size: 256** -- Optimal GPU utilization -- Reasonable latency (<2s for batch processing) -- Balances throughput vs. freshness - -### 3. **In-Memory vs. Database** -✅ Started with in-memory (via Repository pattern) -- Faster iteration -- Easy to add persistence later -- Pattern makes swap trivial - -### 4. **Fuzzy vs. Hard Clustering** -✅ Fuzzy C-Means: -- Better for real-world segmentation -- Customers often span multiple segments -- Provides confidence scores - -## Technical Challenges Solved - -1. **Type Inference with fs2 + Cats** - - Issue: Pattern matching in `traverse` lost type information - - Solution: Explicit type annotations + `.covary[IO]` - -2. **GPU Memory Management** - - GCluster handles allocation/deallocation automatically - - Array-based APIs (no manual ByteBuffer management) - -3. **Async Pipeline Testing** - - Challenge: Pipeline processes asynchronously in batches - - Current: Some tests have timing issues (acceptable for demo) - - Production: Would use proper synchronization - -## Future Enhancements - -### Phase 2 (Production-Ready) -- PostgreSQL + Doobie for persistence -- Kafka for transaction ingestion -- Scheduled batch jobs for global reclustering -- Observability (Prometheus metrics, Jaeger tracing) - -### Phase 3 (Scale) -- Distributed clustering (Spark + GPU) -- Feature store integration -- A/B testing for segment definitions -- Real-time segment change events (via Kafka) - -## Conclusion - -This microservice demonstrates: -- ✅ **fs2 mastery**: Complex streaming pipeline with GPU integration -- ✅ **Clean architecture**: Repository pattern, separation of concerns -- ✅ **GPU acceleration**: Real compute-intensive workload -- ✅ **Production patterns**: HTTP API, health checks, Swagger docs -- ✅ **Functional programming**: Pure FP with cats-effect - -The code is **production-style**, not a toy example, while remaining **concise and readable**. diff --git a/cyfra-analytics/README.md b/cyfra-analytics/README.md deleted file mode 100644 index 179ae83b..00000000 --- a/cyfra-analytics/README.md +++ /dev/null @@ -1,189 +0,0 @@ -# Customer Segmentation Microservice - -GPU-accelerated customer segmentation using continuous Fuzzy C-Means clustering with fs2 streaming. - -## Architecture - -### Clean Separation of Concerns - -``` -├── model/ Domain models (Transaction, CustomerProfile, CustomerSegment) -├── repository/ Data persistence layer -│ ├── CustomerProfileRepository Customer behavioral profiles -│ ├── CustomerSegmentRepository Segment assignments -│ └── CentroidsRepository Segment centroids (configurable!) -├── service/ Business logic -│ ├── FeatureExtractionService Compute RFM + behavioral features -│ ├── DataGenerationService Generate sample data -│ └── SegmentationService Orchestrates GPU clustering pipeline -├── endpoints/ Tapir API definitions -└── server/ HTTP server setup -``` - -### fs2 Streaming Pipeline - -``` -POST /transactions → Queue → fs2 Stream - ↓ - Cache & Extract Features - ↓ - Batch (256 customers) - ↓ - GPU Fuzzy C-Means Clustering - ↓ - Assign Segments → Repository - ↓ - (loop continuously) -``` - -## Features - -### 🎯 **Dynamic Centroids** -Centroids are **not hardcoded** - they're stored in the repository and can be updated via API: - -```bash -# Get current centroids -curl http://localhost:8081/api/v1/centroids - -# Update centroids -curl -X PUT http://localhost:8081/api/v1/centroids \ - -H "Content-Type: application/json" \ - -d '{ - "labels": ["VIP", "Loyal", "Price Sensitive", "New", "At Risk"], - "values": [0.1, 0.9, ..., 0.2] - }' -``` - -### 📊 **Sample Data Generation** -On startup, the service generates **100 sample customers** with **20 transactions each**, pre-distributed across segments. - -### 🗂️ **Separate Repositories** -- **CustomerProfileRepository**: Stores customer behavioral profiles (features, spend, etc.) -- **CustomerSegmentRepository**: Stores segment assignments with fuzzy memberships -- **CentroidsRepository**: Stores segment definitions (centroids) -- **No transaction storage**: Transactions are processed in-flight and cached temporarily - -### 🧩 **Modular Services** -- **FeatureExtractionService**: Standalone feature computation (10 RFM + behavioral metrics) -- **DataGenerationService**: Generates realistic sample data -- **SegmentationService**: Lightweight orchestrator (~165 lines) - -## API Endpoints - -### Submit Transaction -```bash -POST /api/v1/transactions -{ - "customerId": 123, - "timestamp": 1705147800000, - "amount": 149.99, - "items": 3, - "category": 5, - "channel": "mobile_app", - "discountPct": 0.15 -} -``` - -### Get Customer Segment -```bash -GET /api/v1/customers/123 -``` - -Response: -```json -{ - "customerId": 123, - "segment": "VIP Champion", - "confidence": 0.78, - "topSegments": [ - ["VIP Champion", 0.78], - ["Loyal Customer", 0.15], - ["Price Sensitive", 0.07] - ], - "lifetimeValue": 4567.89, - "daysSinceLastTransaction": 2, - "transactionCount": 45 -} -``` - -### List All Segments -```bash -GET /api/v1/segments -``` - -### Get/Update Centroids -```bash -GET /api/v1/centroids -PUT /api/v1/centroids -``` - -### Health Check -```bash -GET /health -``` - -## Running - -```bash -# Start server (auto-generates sample data) -sbt "analytics/run" - -# Server runs on http://localhost:8081 -# Swagger UI at http://localhost:8081/docs - -# Test API -./cyfra-analytics/test-api.ps1 # Windows -./cyfra-analytics/test-api.sh # Linux/Mac -``` - -## Customer Segments - -The service classifies customers into 5 behavioral segments (configurable via API): - -1. **VIP Champion** - High recency, frequency, and monetary value -2. **Loyal Customer** - Consistent purchasers with good retention -3. **Price Sensitive** - Discount-driven, shops on deals -4. **New Explorer** - Recent acquisition, exploring catalog -5. **At Risk** - Low recency, needs re-engagement - -## Technical Details - -- **Features**: 10-dimensional (RFM + order metrics + behavioral patterns) -- **Clustering**: Fuzzy C-Means with fuzziness=2.0, 10 iterations per batch -- **Batch Size**: 256 customers processed together on GPU -- **Sample Data**: 100 customers, 20 transactions each, generated on startup -- **Pipeline**: Continuous fs2 stream with GPU acceleration via `GCluster` - -## Architecture Improvements - -### ✅ Separated Repositories -- `CustomerProfileRepository` - Behavioral profiles -- `CustomerSegmentRepository` - Segment assignments -- `CentroidsRepository` - Configurable centroids - -### ✅ Extracted Services -- `FeatureExtractionService` - Standalone feature computation -- `DataGenerationService` - Sample data generation -- `SegmentationService` - Lightweight orchestrator - -### ✅ No Transaction Storage -Transactions are processed in streaming fashion and cached temporarily (last 50 per customer) for feature extraction. No persistent transaction storage needed. - -### ✅ Configurable Centroids -Centroids stored in repository with PUT endpoint to update them dynamically. No hardcoding! - -## Swagger UI - -API documentation available at: `http://localhost:8081/docs` - -## Tests - -```bash -# Run all tests -sbt "analytics/test" -``` - -Tests cover: -- Sample data generation -- Continuous pipeline processing -- API endpoints (health, segments, centroids) diff --git a/cyfra-analytics/REFACTORING_SUMMARY.md b/cyfra-analytics/REFACTORING_SUMMARY.md deleted file mode 100644 index 80b6ff1f..00000000 --- a/cyfra-analytics/REFACTORING_SUMMARY.md +++ /dev/null @@ -1,195 +0,0 @@ -# Refactoring Summary - -## What Changed - -### ✅ **Repository Separation** - -**Before**: Single `CustomerRepository` handling everything -**After**: Three focused repositories - -```scala -// Separated concerns -CustomerProfileRepository // Behavioral profiles & features -CustomerSegmentRepository // Segment assignments & stats -CentroidsRepository // Configurable segment definitions -``` - -**Benefits**: -- Single Responsibility Principle -- Easy to swap implementations (PostgreSQL, Redis, etc.) -- Clearer dependencies - -### ✅ **Service Extraction** - -**Before**: `SegmentationService` was 197 lines with mixed concerns -**After**: Three focused services - -```scala -FeatureExtractionService // 56 lines - Pure feature computation -DataGenerationService // 67 lines - Sample data generation -SegmentationService // 165 lines - Pipeline orchestration -``` - -**Benefits**: -- Each service has one job -- Easier to test in isolation -- Better code organization - -### ✅ **Removed Unnecessary Code** - -**Deleted**: -- ❌ `EcommerceEvents.scala` - Not needed (duplicate definitions) -- ❌ `CustomerRepository.scala` - Replaced with focused repositories -- ❌ `InMemoryCustomerRepository.scala` - Split into 3 repositories -- ❌ Transaction storage - Transactions processed in-flight, cached temporarily - -**Why**: Transactions don't need persistent storage - they're processed streaming and we cache the last 50 per customer for feature extraction. - -### ✅ **Dynamic Centroids** - -**Before**: Hardcoded in service -```scala -// BAD - hardcoded -private val SegmentCentroids = FCMCentroids(...) -``` - -**After**: Stored in repository with API to update -```scala -// GOOD - configurable via repository -centroidsRepo.get // GET /api/v1/centroids -centroidsRepo.update(...) // PUT /api/v1/centroids -``` - -**Benefits**: -- Business users can adjust segments without code changes -- A/B test different segment definitions -- Production-ready pattern - -### ✅ **Sample Data Generation** - -**Before**: Empty database on startup -**After**: Auto-generates 100 customers with 20 transactions each - -```scala -// In server startup: -dataGen.generateSampleData(numCustomers = 100, transactionsPerCustomer = 20) -``` - -**Benefits**: -- Immediate demo capability -- Realistic data distribution across 5 segments -- No manual data loading needed - -## New API Endpoints - -### GET `/api/v1/centroids` -```json -{ - "labels": ["VIP Champion", "Loyal Customer", ...], - "numClusters": 5, - "numFeatures": 10 -} -``` - -### PUT `/api/v1/centroids` -```json -{ - "labels": ["VIP", "Loyal", "Price", "New", "Risk"], - "values": [0.1, 0.9, ..., 0.2] -} -``` - -## Architecture Comparison - -### Before -``` -SegmentationService (197 lines) - ├─ Feature extraction logic - ├─ Clustering pipeline - ├─ Hardcoded centroids - └─ Repository access - -CustomerRepository - ├─ Profiles - ├─ Segments - └─ Transactions -``` - -### After -``` -SegmentationService (165 lines) - └─ Pipeline orchestration only - -FeatureExtractionService (56 lines) - └─ Pure feature computation - -DataGenerationService (67 lines) - └─ Sample data generation - -CustomerProfileRepository - └─ Profiles only - -CustomerSegmentRepository - └─ Segments only - -CentroidsRepository - └─ Configurable centroids -``` - -## File Structure - -``` -cyfra-analytics/src/main/scala/io/computenode/cyfra/analytics/ -├── model/ -│ ├── Domain.scala # Core domain models -│ └── CentroidsUpdate.scala # NEW - Centroids API models -├── repository/ -│ ├── CustomerProfileRepository.scala # NEW - Profile trait -│ ├── InMemoryProfileRepository.scala # NEW - Profile impl -│ ├── CustomerSegmentRepository.scala # NEW - Segment trait -│ ├── InMemorySegmentRepository.scala # NEW - Segment impl -│ ├── CentroidsRepository.scala # NEW - Centroids trait -│ └── InMemoryCentroidsRepository.scala # NEW - Centroids impl -├── service/ -│ ├── FeatureExtractionService.scala # NEW - Extracted -│ ├── DataGenerationService.scala # NEW - Created -│ └── SegmentationService.scala # REFACTORED - Smaller -├── endpoints/ -│ └── SegmentationEndpoints.scala # UPDATED - +2 endpoints -└── server/ - └── SegmentationServer.scala # UPDATED - Data gen on startup -``` - -## Benefits Summary - -1. **Cleaner Architecture** - Separation of concerns -2. **More Testable** - Smaller, focused units -3. **More Flexible** - Dynamic centroids via API -4. **Better UX** - Sample data on startup -5. **Less Code** - Removed unnecessary transaction storage -6. **Production-Ready** - Repository pattern enables easy DB swap - -## Running - -```bash -# Start server (auto-generates sample data) -sbt "analytics/run" - -# Logs show: -# - Generated 100 sample customers with 20 transactions each -# - Started continuous segmentation pipeline -# - Server started at http://localhost:8081 - -# Try the API -curl http://localhost:8081/api/v1/segments -curl http://localhost:8081/api/v1/centroids -``` - -## Tests - -All tests passing ✅ - -```bash -sbt "analytics/test" -# [info] Passed: Total 5, Failed 0, Errors 0, Passed 5 -``` diff --git a/cyfra-analytics/test-api.ps1 b/cyfra-analytics/test-api.ps1 deleted file mode 100644 index 80e356c3..00000000 --- a/cyfra-analytics/test-api.ps1 +++ /dev/null @@ -1,69 +0,0 @@ -$API = "http://localhost:8081/api/v1" - -Write-Host "=== Customer Segmentation API Test ===" -ForegroundColor Cyan -Write-Host - -Write-Host "1. Health Check" -ForegroundColor Yellow -Invoke-RestMethod -Uri "$API/../health" -Method Get | ConvertTo-Json -Write-Host - -Write-Host "2. Submit Transactions for Multiple Customers" -ForegroundColor Yellow -for ($i = 1; $i -le 300; $i++) { - $customerId = 1 + ($i % 10) - $amount = 50 + (($i % 100) * 5) - $timestamp = [DateTimeOffset]::UtcNow.ToUnixTimeMilliseconds() - ($i * 100000) - $category = $i % 20 - $channel = if ($i % 3 -eq 0) { "mobile_app" } else { "web" } - $discount = if ($i % 4 -eq 0) { 0.15 } else { 0.0 } - - $body = @{ - customerId = $customerId - timestamp = $timestamp - amount = $amount - items = 1 + ($i % 5) - category = $category - channel = $channel - discountPct = $discount - } | ConvertTo-Json - - Invoke-RestMethod -Uri "$API/transactions" -Method Post -Body $body -ContentType "application/json" | Out-Null - - if ($i % 50 -eq 0) { - Write-Host " Submitted $i transactions..." - } -} -Write-Host " All transactions submitted!" -ForegroundColor Green -Write-Host - -Write-Host "3. Wait for processing..." -ForegroundColor Yellow -Start-Sleep -Seconds 3 -Write-Host - -Write-Host "4. Get Customer 1 Segment" -ForegroundColor Yellow -Invoke-RestMethod -Uri "$API/customers/1" -Method Get | ConvertTo-Json -Depth 5 -Write-Host - -Write-Host "5. Get Customer 5 Segment" -ForegroundColor Yellow -Invoke-RestMethod -Uri "$API/customers/5" -Method Get | ConvertTo-Json -Depth 5 -Write-Host - -Write-Host "6. List All Segments" -ForegroundColor Yellow -$segments = Invoke-RestMethod -Uri "$API/segments" -Method Get -$segments.segments | ForEach-Object { - [PSCustomObject]@{ - Name = $_.name - CustomerCount = $_.customerCount - AvgLifetimeValue = [math]::Round($_.avgLifetimeValue, 2) - } -} | Format-Table -Write-Host - -Write-Host "7. Get Segment Summary" -ForegroundColor Yellow -[PSCustomObject]@{ - TotalCustomers = $segments.totalCustomers - LastUpdated = $segments.lastUpdated - SegmentCount = $segments.segments.Count -} | ConvertTo-Json -Write-Host - -Write-Host "=== Test Complete ===" -ForegroundColor Cyan diff --git a/cyfra-analytics/test-api.sh b/cyfra-analytics/test-api.sh deleted file mode 100644 index 2df4a611..00000000 --- a/cyfra-analytics/test-api.sh +++ /dev/null @@ -1,60 +0,0 @@ -#!/bin/bash - -API="http://localhost:8081/api/v1" - -echo "=== Customer Segmentation API Test ===" -echo - -echo "1. Health Check" -curl -s "$API/../health" | jq . -echo -e "\n" - -echo "2. Submit Transactions for Multiple Customers" -for i in {1..300}; do - CUSTOMER_ID=$((1 + i % 10)) - AMOUNT=$((50 + (i % 100) * 5)) - TIMESTAMP=$(($(date +%s)000 - i * 100000)) - CATEGORY=$((i % 20)) - CHANNEL=$( [ $((i % 3)) -eq 0 ] && echo "mobile_app" || echo "web" ) - DISCOUNT=$( [ $((i % 4)) -eq 0 ] && echo "0.15" || echo "0.0" ) - - curl -s -X POST "$API/transactions" \ - -H "Content-Type: application/json" \ - -d "{ - \"customerId\": $CUSTOMER_ID, - \"timestamp\": $TIMESTAMP, - \"amount\": $AMOUNT, - \"items\": $((1 + i % 5)), - \"category\": $CATEGORY, - \"channel\": \"$CHANNEL\", - \"discountPct\": $DISCOUNT - }" > /dev/null - - if [ $((i % 50)) -eq 0 ]; then - echo " Submitted $i transactions..." - fi -done -echo " All transactions submitted!" -echo - -echo "3. Wait for processing..." -sleep 3 -echo - -echo "4. Get Customer 1 Segment" -curl -s "$API/customers/1" | jq . -echo -e "\n" - -echo "5. Get Customer 5 Segment" -curl -s "$API/customers/5" | jq . -echo -e "\n" - -echo "6. List All Segments" -curl -s "$API/segments" | jq '.segments[] | {name, customerCount, avgLifetimeValue}' -echo -e "\n" - -echo "7. Get Segment Summary" -curl -s "$API/segments" | jq '{totalCustomers, lastUpdated, segmentCount: (.segments | length)}' -echo - -echo "=== Test Complete ===" diff --git a/docs/.gitignore b/docs/.gitignore new file mode 100644 index 00000000..b2d6de30 --- /dev/null +++ b/docs/.gitignore @@ -0,0 +1,20 @@ +# Dependencies +/node_modules + +# Production +/build + +# Generated files +.docusaurus +.cache-loader + +# Misc +.DS_Store +.env.local +.env.development.local +.env.test.local +.env.production.local + +npm-debug.log* +yarn-debug.log* +yarn-error.log* diff --git a/docs/README.md b/docs/README.md new file mode 100644 index 00000000..b28211a9 --- /dev/null +++ b/docs/README.md @@ -0,0 +1,41 @@ +# Website + +This website is built using [Docusaurus](https://docusaurus.io/), a modern static website generator. + +## Installation + +```bash +yarn +``` + +## Local Development + +```bash +yarn start +``` + +This command starts a local development server and opens up a browser window. Most changes are reflected live without having to restart the server. + +## Build + +```bash +yarn build +``` + +This command generates static content into the `build` directory and can be served using any static contents hosting service. + +## Deployment + +Using SSH: + +```bash +USE_SSH=true yarn deploy +``` + +Not using SSH: + +```bash +GIT_USER= yarn deploy +``` + +If you are using GitHub pages for hosting, this command is a convenient way to build the website and push to the `gh-pages` branch. diff --git a/docs/docs/composing-gpu-programs.md b/docs/docs/composing-gpu-programs.md new file mode 100644 index 00000000..9e470496 --- /dev/null +++ b/docs/docs/composing-gpu-programs.md @@ -0,0 +1,247 @@ +--- +sidebar_position: 4 +--- + +# Composing GPU Programs + +While `GFunction` provides a convenient high-level API for array transformations, `GProgram` offers fine-grained control over GPU execution. Programs can be composed into pipelines where the output of one computation feeds into the next, all without transferring data back to the CPU. + +## Anatomy of a GProgram + +A `GProgram` consists of three parts: a layout defining the buffers and uniforms, a dispatch configuration determining how many GPU threads to launch, and a body containing the actual computation. + +Here's a complete example with a program that doubles every element in a buffer: + +```scala +import io.computenode.cyfra.core.{GBufferRegion, GProgram} +import io.computenode.cyfra.core.GProgram.StaticDispatch +import io.computenode.cyfra.core.layout.Layout +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.runtime.VkCyfraRuntime + +case class DoubleLayout(input: GBuffer[Float32], output: GBuffer[Float32]) extends Layout + +@main def simpleProgram(): Unit = + given runtime: VkCyfraRuntime = VkCyfraRuntime() + + val doubleProgram: GProgram[Int, DoubleLayout] = GProgram[Int, DoubleLayout]( + layout = size => DoubleLayout( + input = GBuffer[Float32](size), + output = GBuffer[Float32](size) + ), + dispatch = (_, size) => StaticDispatch(((size + 255) / 256, 1, 1)), + workgroupSize = (256, 1, 1) + ) { layout => + val idx = GIO.invocationId + GIO.when(idx < 256) { + val value = GIO.read(layout.input, idx) + GIO.write(layout.output, idx, value * 2.0f) + } + } + + val size = 256 + val inputData = (0 until size).map(_.toFloat).toArray + val results = Array.ofDim[Float](size) + + GBufferRegion + .allocate[DoubleLayout] + .map { layout => + doubleProgram.execute(size, layout) + } + .runUnsafe( + init = DoubleLayout( + input = GBuffer(inputData), + output = GBuffer[Float32](size) + ), + onDone = layout => layout.output.readArray(results) + ) + + println(s"Input: ${inputData.take(5).mkString(", ")}...") + println(s"Output: ${results.take(5).mkString(", ")}...") + // Output: 0.0, 2.0, 4.0, 6.0, 8.0... + + runtime.close() +``` + +The `layout` function describes what buffers the program needs, parameterized by an `Int` representing the array size. The `dispatch` function specifies how many workgroups to launch—here we divide by 256 (the workgroup size) and round up. The body uses `GIO` operations to read from input, perform the computation, and write to output. + +## Adding Uniform Parameters + +Programs often need configuration that stays constant during execution. Define a struct for your parameters and include it in the layout as a `GUniform`: + +```scala +import io.computenode.cyfra.core.{GBufferRegion, GProgram} +import io.computenode.cyfra.core.layout.Layout +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.runtime.VkCyfraRuntime + +case class MulParams(factor: Float32) extends GStruct[MulParams] + +case class MulLayout( + input: GBuffer[Float32], + output: GBuffer[Float32], + params: GUniform[MulParams] +) extends Layout + +@main def programWithUniforms(): Unit = + given runtime: VkCyfraRuntime = VkCyfraRuntime() + + val mulProgram: GProgram[Int, MulLayout] = GProgram.static[Int, MulLayout]( + layout = size => MulLayout( + input = GBuffer[Float32](size), + output = GBuffer[Float32](size), + params = GUniform[MulParams]() + ), + dispatchSize = size => size + ) { layout => + val idx = GIO.invocationId + GIO.when(idx < 256) { + val value = GIO.read(layout.input, idx) + val factor = layout.params.read.factor + GIO.write(layout.output, idx, value * factor) + } + } + + val size = 256 + val inputData = (0 until size).map(_.toFloat).toArray + val results = Array.ofDim[Float](size) + + GBufferRegion + .allocate[MulLayout] + .map { layout => + mulProgram.execute(size, layout) + } + .runUnsafe( + init = MulLayout( + input = GBuffer(inputData), + output = GBuffer[Float32](size), + params = GUniform(MulParams(3.0f)) + ), + onDone = layout => layout.output.readArray(results) + ) + + println(s"Input: ${inputData.take(5).mkString(", ")}...") + println(s"Output (x * 3): ${results.take(5).mkString(", ")}...") + // Output: 0.0, 3.0, 6.0, 9.0, 12.0... + + runtime.close() +``` + +The `GProgram.static` constructor simplifies dispatch configuration when you just need a linear dispatch based on element count. + +## Building Pipelines + +The real power of `GProgram` comes from composition. You can chain programs together using `GExecution`, creating pipelines where intermediate results stay on the GPU. + +Here's a complete example of a pipeline that first multiplies every element by a factor, then adds a constant: + +```scala +import io.computenode.cyfra.core.{GBufferRegion, GExecution, GProgram} +import io.computenode.cyfra.core.layout.Layout +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.runtime.VkCyfraRuntime + +case class MulParams(factor: Float32) extends GStruct[MulParams] +case class AddParams(addend: Float32) extends GStruct[AddParams] + +case class MulLayout(input: GBuffer[Float32], output: GBuffer[Float32], params: GUniform[MulParams]) extends Layout +case class AddLayout(input: GBuffer[Float32], output: GBuffer[Float32], params: GUniform[AddParams]) extends Layout + +case class MulAddLayout( + input: GBuffer[Float32], + multiplied: GBuffer[Float32], + output: GBuffer[Float32], + mulParams: GUniform[MulParams], + addParams: GUniform[AddParams] +) extends Layout + +@main def pipelineExample(): Unit = + given runtime: VkCyfraRuntime = VkCyfraRuntime() + + val mulProgram: GProgram[Int, MulLayout] = GProgram.static[Int, MulLayout]( + layout = size => MulLayout( + input = GBuffer[Float32](size), + output = GBuffer[Float32](size), + params = GUniform[MulParams]() + ), + dispatchSize = size => size + ) { layout => + val idx = GIO.invocationId + GIO.when(idx < 256) { + val value = GIO.read(layout.input, idx) + val factor = layout.params.read.factor + GIO.write(layout.output, idx, value * factor) + } + } + + val addProgram: GProgram[Int, AddLayout] = GProgram.static[Int, AddLayout]( + layout = size => AddLayout( + input = GBuffer[Float32](size), + output = GBuffer[Float32](size), + params = GUniform[AddParams]() + ), + dispatchSize = size => size + ) { layout => + val idx = GIO.invocationId + GIO.when(idx < 256) { + val value = GIO.read(layout.input, idx) + val addend = layout.params.read.addend + GIO.write(layout.output, idx, value + addend) + } + } + + // Compose into a pipeline: multiply then add + val mulAddPipeline: GExecution[Int, MulAddLayout, MulAddLayout] = + GExecution[Int, MulAddLayout]() + .addProgram(mulProgram)( + size => size, + layout => MulLayout(layout.input, layout.multiplied, layout.mulParams) + ) + .addProgram(addProgram)( + size => size, + layout => AddLayout(layout.multiplied, layout.output, layout.addParams) + ) + + val size = 256 + val inputData = (0 until size).map(_.toFloat).toArray + val results = Array.ofDim[Float](size) + + GBufferRegion + .allocate[MulAddLayout] + .map { layout => + mulAddPipeline.execute(size, layout) + } + .runUnsafe( + init = MulAddLayout( + input = GBuffer(inputData), + multiplied = GBuffer[Float32](size), + output = GBuffer[Float32](size), + mulParams = GUniform(MulParams(3.0f)), + addParams = GUniform(AddParams(100.0f)) + ), + onDone = layout => layout.output.readArray(results) + ) + + println("Pipeline: input -> multiply by 3 -> add 100") + println(s"Input: ${inputData.take(5).mkString(", ")}...") + println(s"Output: ${results.take(5).mkString(", ")}...") + // Output: 100.0, 103.0, 106.0, 109.0, 112.0... + + runtime.close() +``` + +Each `addProgram` call specifies how to map the pipeline's parameters to the program's parameters, and how to extract the program's layout from the pipeline's layout. The multiply program writes to `multiplied`, which the add program then reads from. The intermediate buffer never leaves the GPU. + +## When to Use GProgram vs GFunction + +`GFunction` is the right choice when you have a straightforward array transformation and want minimal boilerplate. It handles buffer management, dispatch configuration, and data transfer automatically. + +`GProgram` becomes necessary when you need: + +- Multiple passes over data without CPU round-trips +- Complex buffer layouts with multiple inputs and outputs +- Fine control over workgroup sizes and dispatch dimensions +- Integration with existing SPIR-V shaders + +The two approaches complement each other. In fact, `GFunction` is implemented on top of `GProgram` internally, adding convenience at the cost of flexibility. + diff --git a/docs/docs/examples.md b/docs/docs/examples.md new file mode 100644 index 00000000..f2a0c8a5 --- /dev/null +++ b/docs/docs/examples.md @@ -0,0 +1,6 @@ +--- +sidebar_position: 5 +--- + +# Examples + diff --git a/docs/docs/getting-started.md b/docs/docs/getting-started.md new file mode 100644 index 00000000..1cde8166 --- /dev/null +++ b/docs/docs/getting-started.md @@ -0,0 +1,75 @@ +--- +sidebar_position: 2 +--- + +# Getting Started + +This guide will help you set up Cyfra and run your first GPU computation in minutes. + +## Requirements + +Cyfra requires a system with Vulkan support. Most modern GPUs from NVIDIA, AMD, and Intel work out of the box. You'll also need: + +- JDK 21 or later +- sbt 1.9 or later +- Vulkan SDK installed on your system + +## Installation + +Add Cyfra to your `build.sbt`: + +```scala +libraryDependencies ++= Seq( + "io.computenode" %% "cyfra-foton" % "0.1.0" // Coming soon +) +``` + +:::note +Cyfra is not yet published to Maven Central. For now, clone the repository and publish locally: + +```bash +git clone https://github.com/computenode/cyfra.git +cd cyfra +sbt publishLocal +``` +::: + +## Quick Start + +Here's a complete example that doubles an array of numbers on the GPU: + +```scala +import io.computenode.cyfra.core.CyfraRuntime +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.foton.GFunction +import io.computenode.cyfra.runtime.VkCyfraRuntime + +@main def quickStart(): Unit = + // Initialize the Vulkan runtime + given CyfraRuntime = VkCyfraRuntime() + + // Define a GPU function + val doubleIt = GFunction[Float32, Float32] { x => + x * 2.0f + } + + // Run it + val input = Array(1.0f, 2.0f, 3.0f, 4.0f, 5.0f) + val result = doubleIt.run(input) + + println(result.mkString(", ")) + // Output: 2.0, 4.0, 6.0, 8.0, 10.0 + + summon[CyfraRuntime].asInstanceOf[VkCyfraRuntime].close() +``` + +That's it. The lambda `x => x * 2.0f` is compiled to SPIR-V, uploaded to the GPU, and executed in parallel across all elements. + +## Next Steps + +Now that you have Cyfra running, explore the core concepts: + +- **[GPU Functions](/docs/gpu-functions)** — Learn how to write and configure GPU functions +- **[Composing GPU Programs](/docs/composing-gpu-programs)** — Build multi-pass pipelines that keep data on the GPU +- **[Examples](/docs/examples)** — See complete examples including fractals and simulations + diff --git a/docs/docs/gpu-functions.md b/docs/docs/gpu-functions.md new file mode 100644 index 00000000..e6254fba --- /dev/null +++ b/docs/docs/gpu-functions.md @@ -0,0 +1,179 @@ +--- +sidebar_position: 3 +--- + +# GPU Functions + +A `GFunction` represents a function that runs on the GPU, transforming an input array into an output array in parallel. Think of it as a GPU-accelerated `map` operation where each element is processed independently by a separate GPU thread. + +## Your First GPU Function + +The simplest way to create a GPU function is by passing a lambda that describes how to transform a single element: + +```scala +import io.computenode.cyfra.core.CyfraRuntime +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.foton.GFunction +import io.computenode.cyfra.runtime.VkCyfraRuntime + +@main def helloGpu(): Unit = + given CyfraRuntime = VkCyfraRuntime() + + val doubleIt: GFunction[GStruct.Empty, Float32, Float32] = GFunction { x => + x * 2.0f + } + + val input = (0 until 256).map(_.toFloat).toArray + val result: Array[Float] = doubleIt.run(input) + + println(s"Input: ${input.take(5).mkString(", ")}...") + println(s"Output: ${result.take(5).mkString(", ")}...") + // Output: 0.0, 2.0, 4.0, 6.0, 8.0... + + summon[CyfraRuntime].asInstanceOf[VkCyfraRuntime].close() +``` + +This creates a function that doubles every element. The type signature `GFunction[GStruct.Empty, Float32, Float32]` indicates that it takes no configuration parameters (`GStruct.Empty`), accepts `Float32` values as input, and produces `Float32` values as output. + +The entire array is processed in parallel on the GPU. Each invocation of the lambda operates on a different element, with thousands of GPU threads working simultaneously. + +## Working with Vectors + +Cyfra provides built-in vector types that map directly to GPU hardware. The `Vec4[Float32]` type represents a 4-component floating-point vector and supports standard operations like normalization and dot products: + +```scala +import io.computenode.cyfra.core.CyfraRuntime +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.foton.GFunction +import io.computenode.cyfra.runtime.VkCyfraRuntime + +@main def vectorOperations(): Unit = + given CyfraRuntime = VkCyfraRuntime() + + val normalizeVec4: GFunction[GStruct.Empty, Vec4[Float32], Vec4[Float32]] = GFunction { v => + normalize(v) + } + + val dotWithX: GFunction[GStruct.Empty, Vec4[Float32], Float32] = GFunction { v => + val xAxis = vec4(1.0f, 0.0f, 0.0f, 0.0f) + v.dot(xAxis) + } + + // On the Scala side, Vec4 maps to (Float, Float, Float, Float) tuples + val vectors: Array[(Float, Float, Float, Float)] = Array( + (3.0f, 0.0f, 0.0f, 0.0f), + (0.0f, 4.0f, 0.0f, 0.0f), + (1.0f, 1.0f, 1.0f, 1.0f) + ) ++ Array.fill(253)((1.0f, 0.0f, 0.0f, 0.0f)) + + val normalized = normalizeVec4.run(vectors) + println(f"(3,0,0,0) normalized: (${normalized(0)._1}%.2f, ${normalized(0)._2}%.2f, ${normalized(0)._3}%.2f, ${normalized(0)._4}%.2f)") + // Output: (1.00, 0.00, 0.00, 0.00) + + val dots = dotWithX.run(vectors) + println(s"(3,0,0,0) dot X-axis: ${dots(0)}") + // Output: 3.0 + + summon[CyfraRuntime].asInstanceOf[VkCyfraRuntime].close() +``` + +The codec system handles conversion between Scala tuples and GPU vector types automatically. + +## Configuration with Structs + +Many GPU functions need configuration parameters that remain constant across all elements. Instead of hardcoding values, you can define a configuration struct that gets passed to the GPU as a uniform buffer. + +Define your configuration as a case class extending `GStruct`: + +```scala +import io.computenode.cyfra.core.CyfraRuntime +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.foton.GFunction +import io.computenode.cyfra.runtime.VkCyfraRuntime + +case class TransformConfig(scale: Float32, offset: Float32) extends GStruct[TransformConfig] + +@main def configuredTransform(): Unit = + given CyfraRuntime = VkCyfraRuntime() + + val transform: GFunction[TransformConfig, Float32, Float32] = + GFunction.forEachIndex[TransformConfig, Float32, Float32] { (config, idx, buffer) => + buffer.read(idx) * config.scale + config.offset + } + + val data = (0 until 256).map(_.toFloat).toArray + + // Same compiled GPU code, different configurations + val doubled = transform.run(data, TransformConfig(2.0f, 0.0f)) + println(s"f(x) = x * 2: ${doubled.take(5).mkString(", ")}...") + // Output: 0.0, 2.0, 4.0, 6.0, 8.0... + + val shifted = transform.run(data, TransformConfig(1.0f, 10.0f)) + println(s"f(x) = x + 10: ${shifted.take(5).mkString(", ")}...") + // Output: 10.0, 11.0, 12.0, 13.0, 14.0... + + val combined = transform.run(data, TransformConfig(0.5f, 100.0f)) + println(s"f(x) = 0.5x + 100: ${combined.take(5).mkString(", ")}...") + // Output: 100.0, 100.5, 101.0, 101.5, 102.0... + + summon[CyfraRuntime].asInstanceOf[VkCyfraRuntime].close() +``` + +The `forEachIndex` variant gives you access to the configuration struct, the element index, and the input buffer. The same compiled shader can be reused with different parameter values without recompilation. + +## 2D Processing + +Image processing and grid-based computations work naturally when you compute 2D coordinates from the linear index. Here's a complete example that generates a Julia set fractal: + +```scala +import io.computenode.cyfra.core.CyfraRuntime +import io.computenode.cyfra.dsl.{*, given} +import io.computenode.cyfra.foton.{GFunction, ImageUtility} +import io.computenode.cyfra.runtime.VkCyfraRuntime +import java.nio.file.Paths + +case class JuliaConfig(width: Int32, height: Int32, cReal: Float32, cImag: Float32) + extends GStruct[JuliaConfig] + +@main def juliaFractal(): Unit = + given CyfraRuntime = VkCyfraRuntime() + + val MaxIterations = 256 + val width = 512 + val height = 512 + + val julia: GFunction[JuliaConfig, Int32, Vec4[Float32]] = + GFunction.forEachIndex[JuliaConfig, Int32, Vec4[Float32]] { (config, idx, buffer) => + val pixelIdx = buffer.read(idx) + val px = pixelIdx.mod(config.width) + val py = pixelIdx / config.width + + val zx = px.asFloat / config.width.asFloat * 3.0f - 1.5f + val zy = py.asFloat / config.height.asFloat * 3.0f - 1.5f + + val iterations = GSeq + .gen(vec2(zx, zy), z => + vec2(z.x * z.x - z.y * z.y + config.cReal, 2.0f * z.x * z.y + config.cImag) + ) + .limit(MaxIterations) + .takeWhile(z => z.x * z.x + z.y * z.y < 4.0f) + .count + + val t = iterations.asFloat / MaxIterations.toFloat + vec4(t * t, t, sqrt(t), 1.0f) + } + + val indices = (0 until width * height).toArray + val config = JuliaConfig(width, height, -0.7f, 0.27015f) + + println(s"Computing ${width}x${height} Julia set on GPU...") + val colors: Array[(Float, Float, Float, Float)] = julia.run(indices, config) + + ImageUtility.renderToImage(colors, width, height, Paths.get("julia.png")) + println("Saved to julia.png") + + summon[CyfraRuntime].asInstanceOf[VkCyfraRuntime].close() +``` + +Each pixel is calculated independently on the GPU. The `GSeq` abstraction provides a functional way to express iterative computations that compile to efficient GPU loops. + diff --git a/docs/docusaurus.config.ts b/docs/docusaurus.config.ts new file mode 100644 index 00000000..f018b0ff --- /dev/null +++ b/docs/docusaurus.config.ts @@ -0,0 +1,94 @@ +import {themes as prismThemes} from 'prism-react-renderer'; +import type {Config} from '@docusaurus/types'; +import type * as Preset from '@docusaurus/preset-classic'; + +const config: Config = { + title: 'Cyfra', + tagline: 'GPU programming in Scala', + favicon: 'img/favicon.ico', + + future: { + v4: true, + }, + + url: 'https://cyfra.computenode.io', + baseUrl: '/', + + trailingSlash: false, + + + organizationName: 'computenode', + projectName: 'cyfra', + + onBrokenLinks: 'throw', + + i18n: { + defaultLocale: 'en', + locales: ['en'], + }, + + presets: [ + [ + 'classic', + { + docs: { + sidebarPath: './sidebars.ts', + }, + blog: false, + theme: { + customCss: './src/css/custom.css', + }, + } satisfies Preset.Options, + ], + ], + + themeConfig: { + colorMode: { + defaultMode: 'dark', + disableSwitch: true, + respectPrefersColorScheme: false, + }, + navbar: { + title: 'Cyfra', + items: [ + { + type: 'docSidebar', + sidebarId: 'docsSidebar', + position: 'left', + label: 'Docs', + }, + { + href: 'https://github.com/computenode/cyfra', + label: 'GitHub', + position: 'right', + }, + ], + }, + footer: { + style: 'dark', + links: [ + { + title: 'Docs', + items: [ + { + label: 'Getting Started', + to: '/docs/getting-started', + }, + ], + }, + ], + copyright: `Copyright © ${new Date().getFullYear()} Cyfra. Built with Docusaurus.`, + }, + prism: { + theme: prismThemes.dracula, + darkTheme: prismThemes.dracula, + additionalLanguages: ['java', 'scala', 'bash'], + }, + } satisfies Preset.ThemeConfig, +}; + +export default config; + + + + diff --git a/docs/package-lock.json b/docs/package-lock.json new file mode 100644 index 00000000..1f0d4929 --- /dev/null +++ b/docs/package-lock.json @@ -0,0 +1,18113 @@ +{ + "name": "docs", + "version": "0.0.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "docs", + "version": "0.0.0", + "dependencies": { + "@docusaurus/core": "3.9.2", + "@docusaurus/preset-classic": "3.9.2", + "@mdx-js/react": "^3.0.0", + "clsx": "^2.0.0", + "prism-react-renderer": "^2.3.0", + "react": "^19.0.0", + "react-dom": "^19.0.0" + }, + "devDependencies": { + "@docusaurus/module-type-aliases": "3.9.2", + "@docusaurus/tsconfig": "3.9.2", + "@docusaurus/types": "3.9.2", + "typescript": "~5.6.2" + }, + "engines": { + "node": ">=20.0" + } + }, + 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diff --git a/docs/package.json b/docs/package.json new file mode 100644 index 00000000..e61ba2b7 --- /dev/null +++ b/docs/package.json @@ -0,0 +1,47 @@ +{ + "name": "docs", + "version": "0.0.0", + "private": true, + "scripts": { + "docusaurus": "docusaurus", + "start": "docusaurus start", + "build": "docusaurus build", + "swizzle": "docusaurus swizzle", + "deploy": "docusaurus deploy", + "clear": "docusaurus clear", + "serve": "docusaurus serve", + "write-translations": "docusaurus write-translations", + "write-heading-ids": "docusaurus write-heading-ids", + "typecheck": "tsc" + }, + "dependencies": { + "@docusaurus/core": "3.9.2", + "@docusaurus/preset-classic": "3.9.2", + "@mdx-js/react": "^3.0.0", + "clsx": "^2.0.0", + "prism-react-renderer": "^2.3.0", + "react": "^19.0.0", + "react-dom": "^19.0.0" + }, + "devDependencies": { + "@docusaurus/module-type-aliases": "3.9.2", + "@docusaurus/tsconfig": "3.9.2", + "@docusaurus/types": "3.9.2", + "typescript": "~5.6.2" + }, + "browserslist": { + "production": [ + ">0.5%", + "not dead", + "not op_mini all" + ], + "development": [ + "last 3 chrome version", + "last 3 firefox version", + "last 5 safari version" + ] + }, + "engines": { + "node": ">=20.0" + } +} diff --git a/docs/sidebars.ts b/docs/sidebars.ts new file mode 100644 index 00000000..2d0a486a --- /dev/null +++ b/docs/sidebars.ts @@ -0,0 +1,12 @@ +import type {SidebarsConfig} from '@docusaurus/plugin-content-docs'; + +const sidebars: SidebarsConfig = { + docsSidebar: [ + 'getting-started', + 'gpu-functions', + 'composing-gpu-programs', + 'examples', + ], +}; + +export default sidebars; diff --git a/docs/src/css/custom.css b/docs/src/css/custom.css new file mode 100644 index 00000000..bf713391 --- /dev/null +++ b/docs/src/css/custom.css @@ -0,0 +1,77 @@ +/** + * Cyfra Documentation Theme - Dark Only + */ + +:root { + --ifm-color-primary: #f97316; + --ifm-color-primary-dark: #ea580c; + --ifm-color-primary-darker: #c2410c; + --ifm-color-primary-darkest: #9a3412; + --ifm-color-primary-light: #fb923c; + --ifm-color-primary-lighter: #fdba74; + --ifm-color-primary-lightest: #fed7aa; + --ifm-background-color: #0c0a09; + --ifm-background-surface-color: #1c1917; + --ifm-code-font-size: 95%; + --docusaurus-highlighted-code-line-bg: rgba(234, 88, 12, 0.2); + --ifm-footer-background-color: #0c0a09; + --ifm-footer-color: #a8a29e; + --ifm-footer-link-color: #d6d3d1; + --ifm-footer-title-color: #fafaf9; +} + +/* Navbar */ +.navbar { + background-color: #0c0a09; + box-shadow: none; + border-bottom: 1px solid #292524; +} + +.navbar__title { + color: #fafaf9; +} + +.navbar__link { + color: #d6d3d1; +} + +.navbar__link:hover { + color: #fafaf9; +} + +/* Footer */ +.footer { + background-color: #0c0a09; + border-top: 1px solid #292524; +} + +.footer--dark { + --ifm-footer-background-color: #0c0a09; + background-color: #0c0a09; +} + +.footer__title { + color: #fafaf9; +} + +.footer__link-item { + color: #a8a29e; +} + +.footer__link-item:hover { + color: #fafaf9; +} + +.footer__copyright { + color: #78716c; +} + +/* Style links */ +a:hover { + text-decoration: none; +} + +/* Code blocks */ +.prism-code { + font-family: "JetBrains Mono", "Fira Code", "Consolas", monospace; +} diff --git a/docs/src/pages/index.tsx b/docs/src/pages/index.tsx new file mode 100644 index 00000000..409ac81c --- /dev/null +++ b/docs/src/pages/index.tsx @@ -0,0 +1,780 @@ +import type { ReactNode } from 'react'; +import Link from '@docusaurus/Link'; +import useDocusaurusContext from '@docusaurus/useDocusaurusContext'; +import Layout from '@theme/Layout'; +import Heading from '@theme/Heading'; + +// Syntax highlighting colors +const syn = { + keyword: '#f97316', + type: '#fbbf24', + string: '#a3e635', + number: '#60a5fa', + comment: '#6b7280', + func: '#c4b5fd', + plain: '#e7e5e4', +}; + +const styles = { + heroSection: { + position: 'relative' as const, + display: 'flex', + alignItems: 'center', + justifyContent: 'center', + padding: '6rem 2rem 5rem', + overflow: 'hidden', + background: '#0c0a09', + }, + heroBackground: { + position: 'absolute' as const, + inset: 0, + background: ` + radial-gradient(ellipse 60% 40% at 50% 0%, rgba(234, 88, 12, 0.12), transparent), + radial-gradient(ellipse 40% 30% at 80% 70%, rgba(220, 38, 38, 0.08), transparent) + `, + }, + gridPattern: { + position: 'absolute' as const, + inset: 0, + backgroundImage: ` + linear-gradient(rgba(255, 255, 255, 0.015) 1px, transparent 1px), + linear-gradient(90deg, rgba(255, 255, 255, 0.015) 1px, transparent 1px) + `, + backgroundSize: '80px 80px', + maskImage: 'radial-gradient(ellipse 80% 60% at 50% 0%, black, transparent 70%)', + }, + heroContent: { + position: 'relative' as const, + zIndex: 10, + textAlign: 'center' as const, + padding: '2rem', + maxWidth: '800px', + }, + heroTitle: { + fontSize: 'clamp(3rem, 8vw, 5.5rem)', + fontWeight: 700, + letterSpacing: '-0.03em', + marginBottom: '0.75rem', + color: '#fafaf9', + }, + heroTagline: { + fontSize: 'clamp(1.1rem, 2.5vw, 1.4rem)', + color: '#a8a29e', + fontWeight: 400, + marginBottom: '2rem', + lineHeight: 1.6, + }, + betaBadge: { + display: 'inline-block', + background: 'rgba(234, 88, 12, 0.15)', + color: '#fb923c', + padding: '0.5rem 1rem', + borderRadius: '6px', + fontSize: '0.85rem', + fontWeight: 500, + marginBottom: '2rem', + border: '1px solid rgba(234, 88, 12, 0.3)', + }, + heroButtons: { + display: 'flex', + gap: '1rem', + justifyContent: 'center', + flexWrap: 'wrap' as const, + }, + primaryButton: { + background: '#ea580c', + color: '#fff', + padding: '0.875rem 2rem', + borderRadius: '8px', + fontSize: '1rem', + fontWeight: 600, + textDecoration: 'none', + display: 'inline-flex', + alignItems: 'center', + gap: '0.5rem', + transition: 'background 0.2s ease', + border: 'none', + }, + secondaryButton: { + background: 'transparent', + color: '#fafaf9', + padding: '0.875rem 2rem', + borderRadius: '8px', + fontSize: '1rem', + fontWeight: 500, + textDecoration: 'none', + display: 'inline-flex', + alignItems: 'center', + gap: '0.5rem', + transition: 'all 0.2s ease', + border: '1px solid #44403c', + }, + + section: { + padding: '5rem 2rem', + background: '#0c0a09', + }, + sectionAlt: { + padding: '5rem 2rem', + background: '#0a0908', + }, + container: { + maxWidth: '1100px', + margin: '0 auto', + }, + sectionTitle: { + fontSize: 'clamp(1.75rem, 4vw, 2.5rem)', + fontWeight: 600, + textAlign: 'center' as const, + marginBottom: '0.75rem', + color: '#fafaf9', + letterSpacing: '-0.02em', + }, + sectionSubtitle: { + fontSize: '1.1rem', + color: '#a8a29e', + textAlign: 'center' as const, + marginBottom: '3rem', + maxWidth: '600px', + margin: '0 auto 3rem', + }, + + featuresGrid: { + display: 'grid', + gridTemplateColumns: 'repeat(auto-fit, minmax(280px, 1fr))', + gap: '1.25rem', + marginTop: '2.5rem', + }, + featureCard: { + background: '#1c1917', + border: '1px solid #292524', + borderRadius: '12px', + padding: '1.5rem', + }, + featureTitle: { + fontSize: '1.1rem', + fontWeight: 600, + color: '#fafaf9', + marginBottom: '0.5rem', + }, + featureDesc: { + color: '#a8a29e', + lineHeight: 1.6, + fontSize: '0.9rem', + }, + + // Code snippets section - 2 columns, 3 rows + snippetsGrid: { + display: 'grid', + gridTemplateColumns: 'repeat(2, 1fr)', + gap: '1.25rem', + marginTop: '2.5rem', + }, + snippetCard: { + background: '#1c1917', + border: '1px solid #292524', + borderRadius: '12px', + overflow: 'hidden', + display: 'flex', + flexDirection: 'column' as const, + }, + snippetHeader: { + padding: '0.75rem 1rem', + borderBottom: '1px solid #292524', + display: 'flex', + alignItems: 'center', + gap: '0.5rem', + }, + snippetDot: { + width: '8px', + height: '8px', + borderRadius: '50%', + background: '#ea580c', + }, + snippetTitle: { + fontSize: '0.85rem', + fontWeight: 500, + color: '#fafaf9', + }, + snippetCode: { + padding: '1.25rem', + margin: 0, + background: '#0f0e0d', + fontSize: '0.8rem', + lineHeight: 1.75, + fontFamily: '"JetBrains Mono", "Fira Code", "Consolas", monospace', + overflowX: 'auto' as const, + flex: 1, + }, + snippetDesc: { + padding: '0.875rem 1rem', + borderTop: '1px solid #292524', + color: '#a8a29e', + fontSize: '0.85rem', + lineHeight: 1.5, + }, + + // Showcase with fixed aspect ratio + showcaseGrid: { + display: 'grid', + gridTemplateColumns: 'repeat(2, 1fr)', + gap: '1.5rem', + }, + showcaseItem: { + background: '#1c1917', + border: '1px solid #292524', + borderRadius: '16px', + overflow: 'hidden', + display: 'flex', + flexDirection: 'column' as const, + }, + showcaseMedia: { + width: '100%', + height: '280px', + overflow: 'hidden', + borderBottom: '1px solid #292524', + }, + showcaseGif: { + width: '100%', + height: '100%', + objectFit: 'cover' as const, + display: 'block', + }, + showcaseContent: { + padding: '1.25rem', + flex: 1, + display: 'flex', + flexDirection: 'column' as const, + }, + showcaseLabel: { + display: 'inline-block', + background: 'rgba(234, 88, 12, 0.15)', + color: '#fb923c', + padding: '0.35rem 0.6rem', + borderRadius: '5px', + fontSize: '0.75rem', + fontWeight: 500, + marginBottom: '0.6rem', + border: '1px solid rgba(234, 88, 12, 0.25)', + alignSelf: 'flex-start', + }, + showcaseTitle: { + fontSize: '1.2rem', + fontWeight: 600, + color: '#fafaf9', + marginBottom: '0.5rem', + letterSpacing: '-0.01em', + }, + showcaseDesc: { + color: '#a8a29e', + lineHeight: 1.6, + fontSize: '0.9rem', + marginBottom: '1rem', + flex: 1, + }, + showcaseButtons: { + display: 'flex', + gap: '0.6rem', + flexWrap: 'wrap' as const, + }, + showcaseButton: { + background: 'transparent', + color: '#fafaf9', + padding: '0.5rem 0.875rem', + borderRadius: '6px', + fontSize: '0.8rem', + fontWeight: 500, + textDecoration: 'none', + display: 'inline-flex', + alignItems: 'center', + gap: '0.4rem', + transition: 'all 0.2s ease', + border: '1px solid #44403c', + }, + showcaseButtonPrimary: { + background: '#ea580c', + color: '#fff', + padding: '0.5rem 0.875rem', + borderRadius: '6px', + fontSize: '0.8rem', + fontWeight: 600, + textDecoration: 'none', + display: 'inline-flex', + alignItems: 'center', + gap: '0.4rem', + transition: 'background 0.2s ease', + border: 'none', + }, + showcaseButtonDisabled: { + background: 'transparent', + color: '#57534e', + padding: '0.5rem 0.875rem', + borderRadius: '6px', + fontSize: '0.8rem', + fontWeight: 500, + textDecoration: 'none', + display: 'inline-flex', + alignItems: 'center', + gap: '0.4rem', + border: '1px solid #292524', + cursor: 'default', + }, + showcaseLabelWip: { + display: 'inline-block', + background: 'rgba(113, 113, 122, 0.15)', + color: '#a1a1aa', + padding: '0.35rem 0.6rem', + borderRadius: '5px', + fontSize: '0.75rem', + fontWeight: 500, + marginBottom: '0.6rem', + border: '1px solid rgba(113, 113, 122, 0.25)', + alignSelf: 'flex-start', + }, + + platformSection: { + display: 'flex', + justifyContent: 'center', + gap: '0.75rem', + flexWrap: 'wrap' as const, + marginTop: '3rem', + }, + platformBadge: { + background: '#1c1917', + border: '1px solid #292524', + borderRadius: '8px', + padding: '0.75rem 1.25rem', + display: 'flex', + alignItems: 'center', + gap: '0.5rem', + color: '#d6d3d1', + fontSize: '0.9rem', + fontWeight: 500, + }, + + ctaSection: { + padding: '6rem 2rem', + background: '#0c0a09', + textAlign: 'center' as const, + borderTop: '1px solid #1c1917', + }, + ctaTitle: { + fontSize: 'clamp(1.5rem, 4vw, 2.25rem)', + fontWeight: 600, + color: '#fafaf9', + marginBottom: '1rem', + letterSpacing: '-0.02em', + }, + ctaDesc: { + fontSize: '1.05rem', + color: '#a8a29e', + marginBottom: '2rem', + maxWidth: '500px', + margin: '0 auto 2rem', + }, +}; + +// Helper components for syntax highlighting +const K = ({ children }: { children: ReactNode }) => {children}; +const T = ({ children }: { children: ReactNode }) => {children}; +const S = ({ children }: { children: ReactNode }) => {children}; +const N = ({ children }: { children: ReactNode }) => {children}; +const C = ({ children }: { children: ReactNode }) => {children}; +const F = ({ children }: { children: ReactNode }) => {children}; +const P = ({ children }: { children: ReactNode }) => {children}; + +function HeroSection() { + const { siteConfig } = useDocusaurusContext(); + return ( +
+
+
+
+ + {siteConfig.title} + +

+ GPU compute pipelines in pure Scala 3.
+ Run anywhere. +

+
+ ⚠️ Beta release - not production ready. For experimentation and feedback. +
+
+ + Get Started + + + + + + GitHub + +
+
+
+ ); +} + +function FeaturesSection() { + const features = [ + { + title: 'Pure Scala 3 DSL', + description: 'Write GPU code using familiar Scala syntax. Case classes become GPU structs, functions compile to shaders.', + }, + { + title: 'Vulkan Backend', + description: 'Direct execution on Vulkan-compatible GPUs. NVIDIA, AMD, Intel, and Apple via MoltenVK.', + }, + { + title: 'Composable Pipelines', + description: 'Chain GPU programs together. Intermediate data stays on the GPU. No round-trips to CPU.', + }, + { + title: 'Type-Safe', + description: 'Scala\'s type system catches GPU programming errors at compile time.', + }, + { + title: 'Cross-Platform', + description: 'Linux, Windows, macOS. Write once, run on any Vulkan-capable hardware.', + }, + { + title: 'Zero Overhead', + description: 'Direct compilation to SPIR-V. Your Scala code runs at native GPU speeds.', + }, + ]; + + return ( +
+
+

Why Cyfra?

+

+ GPU programming with the expressiveness of Scala +

+
+ {features.map((feature, idx) => ( +
+

{feature.title}

+

{feature.description}

+
+ ))} +
+
+
+ ); +} + +function CodeSnippetsSection() { + return ( +
+
+

Code That Runs on GPU

+

+ Write Scala. Execute on thousands of GPU cores. +

+
+ {/* Row 1: Vector Operations | Sequence Comprehensions */} +
+
+
+ Vector Operations +
+ 
+val 
normalize
 = GFunction[Vec4[Float32], Vec4[Float32]]:{'\n'}
+{'  '}
v
 => 
v
 / length(
v
){'\n'}
+{'\n'}
+val 
dot
 = GFunction[Vec4[Float32], Float32]:{'\n'}
+{'  '}
v
 => 
v
 dot (1f, 0f, 0f, 0f)
+
+
+ Built-in vector types map to GPU hardware. +
+
+ +
+
+
+ Sequence Comprehensions +
+ 
+val 
iterations
 = GSeq{'\n'}
+{'  '}.gen(vec2(0f, 0f), 
z
 =>{'\n'}
+{'    '}vec2(
z
.
x
*
z
.
x
 - 
z
.
y
*
z
.
y
 + 
cx
, 2f*
z
.
x
*
z
.
y
 + 
cy
)){'\n'}
+{'  '}.limit(256){'\n'}
+{'  '}.takeWhile(
z
 => 
z
.
x
*
z
.
x
 + 
z
.
y
*
z
.
y
 < 4f){'\n'}
+{'  '}.count
+
+
+ Lazy sequences with map, filter, fold. +
+
+ + {/* Row 2: Custom GPU Structs | Monadic GPU Effects */} +
+
+
+ Custom GPU Structs +
+ 
+case class Physics(
gravity
: Float32, 
dt
: Float32){'\n'}
+{'  '}extends GStruct[Physics]{'\n'}
+{'\n'}
+val 
step
 = GFunction.forEachIndex[Physics, Vec4, Vec4]:{'\n'}
+{'  '}(
cfg
, 
i
, 
buf
) =>{'\n'}
+{'    '}val 
p
 = 
buf
.read(
i
){'\n'}
+{'    '}(
p
.
x
, 
p
.
y
 + 
cfg
.
gravity
 * 
cfg
.
dt
, 
p
.
z
, 
p
.
w
)
+
+
+ Case classes become GPU structs. +
+
+ +
+
+
+ Monadic GPU Effects +
+ 
+for{'\n'}
+{'  '}
value
 = 
layout
.
input
.read(
idx
){'\n'}
+{'  '}
_
 <- 
layout
.
bufferA
.write(
idx
, 
value
 + 1f){'\n'}
+{'  '}
_
 <- 
layout
.
bufferB
.write(
idx
, 
value
 * 2f){'\n'}
+yield 
value

+
+
+ Composable GIO monad for effectful computation. +
+
+ + {/* Row 3: GPU Pipelines | GPU Memory Management */} +
+
+
+ GPU Pipelines +
+ 
+val 
pipeline
 = GExecution[Int, Layout](){'\n'}
+{'  '}.addProgram(
multiply
):{'\n'}
+{'    '}
size
 => 
size
{'\n'}
+{'    '}
l
 => MulLayout(
l
.
input
, 
l
.
temp
, 
l
.
mulParams
){'\n'}
+{'  '}.addProgram(
add
):{'\n'}
+{'    '}
size
 => 
size
{'\n'}
+{'    '}
l
 => AddLayout(
l
.
temp
, 
l
.
output
, 
l
.
addParams
)
+
+
+ Chain programs. Data stays on GPU. +
+
+ +
+
+
+ GPU Memory Management +
+ 
+GBufferRegion{'\n'}
+{'  '}.allocate[MyLayout]{'\n'}
+{'  '}.map: 
layout
 =>{'\n'}
+{'    '}
pipeline
.execute(
params
, 
layout
){'\n'}
+{'  '}.runUnsafe({'\n'}
+{'    '}
init
 = MyLayout(GBuffer(
data
), ...),{'\n'}
+{'    '}
onDone
 = 
l
 => 
l
.
output
.readArray(
results
))
+
+
+ Allocate, execute, and read back GPU buffers. +
+
+
+
+
+ ); +} + +function ShowcaseSection() { + return ( +
+
+

See It In Action

+

+ Real projects built with Cyfra +

+ +
+
+
+ Ray traced animation showing reflective spheres +
+
+ GPU programming +

GPU Ray Traced Scenes

+

+ Ray-traced animations with reflections and shadows. The Foton library provides + a clean API for scenes, materials, and camera paths. +

+
+ + View Code + + + Watch Talk + +
+
+
+ +
+
+ Navier-Stokes fluid simulation +
+
+ Complex GPU pipelines +

Navier-Stokes Solver

+

+ Real-time fluid dynamics on the GPU. Multi-stage pipeline solving + Navier-Stokes equations with pressure projection. +

+
+ + View Code + +
+
+
+ +
+
+ GPU customer segmentation animation +
+
+ fs2 + GPU streaming +

Real-time Customer Segmentation

+

+ GPU-accelerated Fuzzy C-Means clustering integrated with fs2 streams. + Process 100k+ transactions/sec with live segment assignment. +

+
+ + View Code + +
+
+
+ +
+
+
+ Coming Soon +
+
+
+ Machine learning +

Machine Learning Library

+

+ Neural network primitives on GPU. Matrix operations, activations, + and automatic differentiation in pure Scala. +

+
+ + View Code + +
+
+
+
+
+
+ ); +} + +function PlatformSection() { + const platforms = [ + { icon: '🐧', name: 'Linux' }, + { icon: '🪟', name: 'Windows' }, + { icon: '🍎', name: 'macOS' }, + { icon: '🎮', name: 'NVIDIA' }, + { icon: '🔴', name: 'AMD' }, + { icon: '🔵', name: 'Intel' }, + ]; + + return ( +
+
+

Runs Everywhere

+

+ Any platform with Vulkan support +

+
+ {platforms.map((platform, idx) => ( +
+ {platform.icon} + {platform.name} +
+ ))} +
+
+
+ ); +} + +function CTASection() { + return ( +
+
+

Try Cyfra Today

+

+ Clone the repo, run the examples, and see what GPU programming in Scala feels like. +

+ + Read the Docs + +
+
+ ); +} + +export default function Home(): ReactNode { + return ( + + +
+ + + + + + +
+ + ); +} diff --git a/docs/static/.nojekyll b/docs/static/.nojekyll new file mode 100644 index 00000000..e69de29b diff --git a/docs/static/CNAME b/docs/static/CNAME new file mode 100644 index 00000000..0dd720fc --- /dev/null +++ b/docs/static/CNAME @@ -0,0 +1 @@ +cyfra.computenode.io diff --git a/docs/static/img/clustering.gif b/docs/static/img/clustering.gif new file mode 100644 index 0000000000000000000000000000000000000000..8ff1ec2af45074fa686ad21f38691118f0aa5cda GIT binary patch literal 1169633 zcmeFZRZyPmwyg^UhY;M|-Q5DgodCguyIXJw?(XjH?jBr&ySux~zyD;6>2t2NPMvkG z&c36H3#wB2`rCSIPwQe5qMTg1gztJl?+HMVkugzFuuw2@P|>haG4N1v@zAgd(QpaT z2=UQK2+>H1&{1(P2uLxA$uTHNG12fbF|aU6sj$$Au+ed_v2d_SNU`b2vFXWin5l5d zsc^aI@G$W4FiG*SaqxH<@NvoU=@{^N=?O5&39u*$s3{3pI0!ND2)XHrF!6}+aESz1 zh%xbqaj1#$afxZkhl8UpCVd0Zu5s(q#krC06u``p&a+1k&kz*5( zV-u1S;gf&ip}=RPAjYR)prPR6qa?wnWMHQh6QjZ=q#`At#wMcS;ib_LpwShjC1ImA z7N#R5r&IVuk4HjJK}0YAnTd#;iIkU#oR^uDmzjc(g@%-cmW0LeGmDcn8xa{B6)&5< 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