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benchmarking: tuned blocksizes; slightly improved performance; mostly improved standard deviation
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Wiplinger Daniel - s2310454043
2025-04-12 13:20:50 +02:00
parent c6e2ce47aa
commit 101ccef67b
5 changed files with 8 additions and 7 deletions
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2
package/src/Interpreter.jl
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@ -33,7 +33,7 @@ function interpret(expressions::Vector{Expr}, variables::Matrix{Float32}, parame
@inbounds for i in eachindex(exprs)
kernel = @cuda launch=false interpret_expression(cudaExprs, cudaVars, cudaParams, cudaResults, cudaStepsize, i)
# config = launch_configuration(kernel.fun)
threads = min(variableCols, 256)
threads = min(variableCols, 128)
blocks = cld(variableCols, threads)
kernel(cudaExprs, cudaVars, cudaParams, cudaResults, cudaStepsize, i; threads, blocks)

2
package/src/Transpiler.jl
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@ -73,7 +73,7 @@ function evaluate(expressions::Vector{Expr}, variables::Matrix{Float32}, paramet
# execute each kernel (also try doing this with Threads.@threads. Since we can have multiple grids, this might improve performance)
for kernel in kernels
# config = launch_configuration(kernels[i])
threads = min(variableCols, 256)
threads = min(variableCols, 96)
blocks = cld(variableCols, threads)
cudacall(kernel, (CuPtr{Float32},CuPtr{Float32},CuPtr{Float32}), cudaVars, cudaParams, cudaResults; threads=threads, blocks=blocks)