Added benchmark files including MLKernels for comparison

Author: theogf

benchmark/MLKernels.jl

@@ -0,0 +1,20 @@
+using MLKernels
+
+SUITE["MLKernels"] = BenchmarkGroup()
+
+mlkernelnames = ["SquaredExponentialKernel"]
+kernels=Dict{String,MLKernels.Kernel}()
+for k in mlkernelnames
+    SUITE["MLKernels"][k] = BenchmarkGroup()
+    kernels[k] = eval(Meta.parse("MLKernels."*k*"(alpha)"))
+end
+
+for k in mlkernelnames
+    SUITE["MLKernels"][k]["k(X,Y)"] = @benchmarkable MLKernels.kernelmatrix($(kernels[k]),$X,$Y)
+    # SUITE["MLKernels"][k][kt]["k!(X,Y)"] = @benchmarkable MLKernels.kernelmatrix!(KXY,$(kernels[k][kt]),$X,$Y) setup=(KXY=copy($KXY))
+    SUITE["MLKernels"][k]["k(X)"] = @benchmarkable MLKernels.kernelmatrix($(kernels[k]),$X)
+    # SUITE["MLKernels"][k][kt]["k!(X)"] = @benchmarkable MLKernels.kernelmatrix!(KX,$(kernels[k][kt]),$X) setup=(KX=copy($KX))
+    # SUITE["MLKernels"][k][kt]["kdiag(X)"] = @benchmarkable MLKernels.kerneldiagmatrix($(kernels[k][kt]),$X)
+    # SUITE["MLKernels"][k][kt]["kdiag!(X)"] = @benchmarkable MLKernels.kerneldiagmatrix!(kX,$(kernels[k][kt]),$X) setup=(kX=copy($kX))
+end
+# results = run(SUITE)

benchmark/benchmarks.jl

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+using BenchmarkTools
+using Random
+using Distances, LinearAlgebra
+
+const SUITE = BenchmarkGroup()
+
+Random.seed!(1234)
+
+dim = 50
+N1 = 1000; N2 = 500;
+alpha = 2.0
+
+X = rand(Float64,N1,dim)
+Y = rand(Float64,N2,dim)
+
+KXY = rand(Float64,N1,N2)
+KX = rand(Float64,N1,N1)
+sKX = Symmetric(rand(Float64,N1,N1))
+kX = rand(Float64,N1)
+
+include("kernelmatrix.jl")
+include("MLKernels.jl")

benchmark/kernelmatrix.jl

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+using KernelFunctions
+
+SUITE["KernelFunctions"] = BenchmarkGroup()
+
+kernelnames = ["SquaredExponentialKernel"]
+kerneltypes = ["ARD","ISO"]
+kernels=Dict{String,Dict{String,KernelFunctions.Kernel}}()
+for k in kernelnames
+    kernels[k] = Dict{String,KernelFunctions.Kernel}()
+    SUITE["KernelFunctions"][k] = BenchmarkGroup()
+    for kt in kerneltypes
+        SUITE["KernelFunctions"][k][kt] = BenchmarkGroup()
+        kernels[k][kt] = eval(Meta.parse("KernelFunctions."*k*"("*(kt == "ARD" ? "alpha*ones(Float64,dim)" : "alpha" )*")"))
+    end
+end
+
+for k in kernelnames
+    for kt in kerneltypes
+        SUITE["KernelFunctions"][k][kt]["k(X,Y)"] = @benchmarkable kernelmatrix($(kernels[k][kt]),$X,$Y,obsdim=1)
+        # SUITE["KernelFunctions"][k][kt]["k!(X,Y)"] = @benchmarkable kernelmatrix!(KXY,$(kernels[k][kt]),$X,$Y) setup=(KXY=copy($KXY))
+        SUITE["KernelFunctions"][k][kt]["k(X)"] = @benchmarkable kernelmatrix($(kernels[k][kt]),$X,obsdim=1)
+        # SUITE["KernelFunctions"][k][kt]["k!(X)"] = @benchmarkable kernelmatrix!(KX,$(kernels[k][kt]),$X) setup=(KX=copy($KX))
+        # SUITE["KernelFunctions"][k][kt]["kdiag(X)"] = @benchmarkable kerneldiagmatrix($(kernels[k][kt]),$X)
+        # SUITE["KernelFunctions"][k][kt]["kdiag!(X)"] = @benchmarkable kerneldiagmatrix!(kX,$(kernels[k][kt]),$X) setup=(kX=copy($kX))
+    end
+end
+# results = run(SUITE)