Refactor GPU allocatable detection into reusable function

Extract the GPU allocatable detection loop into a new NodeHasGpuAllocatable
helper function in utils/gpu/gpu.go. This eliminates code duplication across
gpu_processor.go and makes the logic more maintainable.

The new function returns both the GPU allocatable value and whether it exists,
allowing callers to get both pieces of information in a single call.

Changes:
- Add NodeHasGpuAllocatable() helper in utils/gpu/gpu.go
- Update NodeHasGpu() to use the new helper
- Simplify FilterOutNodesWithUnreadyResources() in gpu_processor.go
- Simplify GetNodeGpuTarget() in gpu_processor.go

Author: DorWeinstock

cluster-autoscaler/processors/customresources/gpu_processor.go

@@ -48,14 +48,7 @@ func (p *GpuCustomResourcesProcessor) FilterOutNodesWithUnreadyResources(autosca
 		}
 
 		_, hasGpuLabel := node.Labels[autoscalingCtx.CloudProvider.GPULabel()]
-		hasAnyGpuAllocatable := false
-		for _, gpuVendorResourceName := range gpu.GPUVendorResourceNames {
-			gpuAllocatable, hasGpuAllocatable := node.Status.Allocatable[gpuVendorResourceName]
-			if hasGpuAllocatable && !gpuAllocatable.IsZero() {
-				hasAnyGpuAllocatable = true
-				break
-			}
-		}
+		_, hasAnyGpuAllocatable := gpu.NodeHasGpuAllocatable(node)
 		if hasGpuLabel && !hasAnyGpuAllocatable {
 			klog.V(3).Infof("Overriding status of node %v, which seems to have unready GPU",
 				node.Name)
@@ -94,10 +87,8 @@ func (p *GpuCustomResourcesProcessor) GetNodeGpuTarget(autoscalingCtx *ca_contex
 		return CustomResourceTarget{}, nil
 	}
 
-	for _, gpuVendorResourceName := range gpu.GPUVendorResourceNames {
-		if gpuAllocatable, found := node.Status.Allocatable[gpuVendorResourceName]; found && gpuAllocatable.Value() > 0 {
-			return CustomResourceTarget{gpuLabel, gpuAllocatable.Value()}, nil
-		}
+	if gpuAllocatableValue, hasGpuAllocatable := gpu.NodeHasGpuAllocatable(node); hasGpuAllocatable {
+		return CustomResourceTarget{gpuLabel, gpuAllocatableValue}, nil
 	}
 
 	// A node is supposed to have GPUs (based on label), but they're not available yet

cluster-autoscaler/utils/gpu/gpu.go

@@ -126,13 +126,20 @@ func NodeHasGpu(GPULabel string, node *apiv1.Node) bool {
 		return true
 	}
 	// Check for extended resources as well
+	_, hasGpuAllocatable := NodeHasGpuAllocatable(node)
+	return hasGpuAllocatable
+}
+
+// NodeHasGpuAllocatable returns the GPU allocatable value and whether the node has GPU allocatable resources.
+// It checks all known GPU vendor resource names and returns the first non-zero allocatable GPU value found.
+func NodeHasGpuAllocatable(node *apiv1.Node) (gpuAllocatableValue int64, hasGpuAllocatable bool) {
 	for _, gpuVendorResourceName := range GPUVendorResourceNames {
-		gpuAllocatable, hasGpuAllocatable := node.Status.Allocatable[gpuVendorResourceName]
-		if hasGpuAllocatable && !gpuAllocatable.IsZero() {
-			return true
+		gpuAllocatable, found := node.Status.Allocatable[gpuVendorResourceName]
+		if found && !gpuAllocatable.IsZero() {
+			return gpuAllocatable.Value(), true
 		}
 	}
-	return false
+	return 0, false
 }
 
 // PodRequestsGpu returns true if a given pod has GPU request.