format

Author: j-fu

benchmarks/sparselu.jl

@@ -8,8 +8,6 @@ BenchmarkTools.DEFAULT_PARAMETERS.seconds = 0.5
 # Why do I need to set this ?
 BenchmarkTools.DEFAULT_PARAMETERS.samples = 10
 
-
-
 # Sparse matrix generation on  a n-dimensional rectangular grid. After
 # https://discourse.julialang.org/t/seven-lines-of-julia-examples-sought/50416/135
 # by A. Braunstein.
@@ -29,15 +27,19 @@ lattice(L...; Tv = Float64) = lattice(L[1]; Tv) ⊕ lattice(L[2:end]...; Tv)
 # Create a matrix similar to that of a finite difference discretization in a `dim`-dimensional
 # unit cube of  ``-Δu + δu`` with approximately N unknowns. It is strictly diagonally dominant.
 #
-function fdmatrix(N; dim=2, Tv = Float64, δ = 1.0e-2)
+function fdmatrix(N; dim = 2, Tv = Float64, δ = 1.0e-2)
     n = N^(1 / dim) |> ceil |> Int
     lattice([n for i in 1:dim]...; Tv) + Tv(δ) * I
 end
 
-
-algs = [UMFPACKFactorization(),KLUFactorization(),MKLPardisoFactorize(),SparspakFactorization()] 
-cols= [:red, :blue, :green, :magenta,:turqoise] # one color per alg
-lst=[:dash,:solid, :dashdot] # one line style per dim
+algs = [
+    UMFPACKFactorization(),
+    KLUFactorization(),
+    MKLPardisoFactorize(),
+    SparspakFactorization(),
+]
+cols = [:red, :blue, :green, :magenta, :turqoise] # one color per alg
+lst = [:dash, :solid, :dashdot] # one line style per dim
 
 __parameterless_type(T) = Base.typename(T).wrapper
 parameterless_type(x) = __parameterless_type(typeof(x))
@@ -48,46 +50,48 @@ parameterless_type(::Type{T}) where {T} = __parameterless_type(T)
 # kmax=15 gives ≈ 328_000 unknows, you can go make a coffee.
 # Main culprit is KLU factorization in 3D.
 #
-function run_and_plot(;dims=[1,2,3], kmax=12)
-
+function run_and_plot(; dims = [1, 2, 3], kmax = 12)
     ns = [10 * 2^k for k in 0:kmax]
-    
-    res = [ [Float64[] for i in 1:length(algs)]  for dim in dims ]
-    
+
+    res = [[Float64[] for i in 1:length(algs)] for dim in dims]
+
     for dim in dims
         for i in 1:length(ns)
             rng = MersenneTwister(123)
-            A = fdmatrix(ns[i];dim)
-            n = size(A,1)
+            A = fdmatrix(ns[i]; dim)
+            n = size(A, 1)
             @info "dim=$(dim): $n × $n"
             b = rand(rng, n)
-            u0= rand(rng, n)
-            
+            u0 = rand(rng, n)
+
             for j in 1:length(algs)
-                bt = @belapsed solve(prob, $(algs[j])).u setup=(prob = LinearProblem(copy($A), copy($b); u0 = copy($u0), alias_A=true, alias_b=true))
+                bt = @belapsed solve(prob, $(algs[j])).u setup=(prob = LinearProblem(copy($A),
+                    copy($b);
+                    u0 = copy($u0),
+                    alias_A = true,
+                    alias_b = true))
                 push!(res[dim][j], bt)
             end
         end
     end
-    
+
     p = plot(;
-             ylabel = "Time/s",
-             xlabel = "N",
-             yscale=:log10,
-             xscale=:log10,
-             title = "Time for NxN  sparse LU Factorization",
-             label = string(Symbol(parameterless_type(algs[1]))),
-             legend=:outertopright)
+        ylabel = "Time/s",
+        xlabel = "N",
+        yscale = :log10,
+        xscale = :log10,
+        title = "Time for NxN  sparse LU Factorization",
+        label = string(Symbol(parameterless_type(algs[1]))),
+        legend = :outertopright)
 
     for dim in dims
         for i in 1:length(algs)
             plot!(p, ns, res[dim][i];
-                  linecolor=cols[i],
-                  linestyle= lst[dim],
-                  label = "$(string(Symbol(parameterless_type(algs[i])))) $(dim)D"  )
+                linecolor = cols[i],
+                linestyle = lst[dim],
+                label = "$(string(Symbol(parameterless_type(algs[i])))) $(dim)D")
         end
     end
     savefig("sparselubench.png")
     savefig("sparselubench.pdf")
 end
-