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Improve block and thread calculations and invoke only if in range #76

Merged
merged 1 commit into from
Apr 18, 2024
Merged

Improve block and thread calculations and invoke only if in range #76

merged 1 commit into from
Apr 18, 2024

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PhilipFackler
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This only applies to 1d parallel_for in CUDA. If this is acceptable to you all, a similar thing should be done where else it's applicable.

@PhilipFackler
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PhilipFackler commented Apr 18, 2024 •
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See #57. This is a problem in 1d also. It's actually not "wrong". It's just that if your N is greater than the threads per block and not divisible by the same, you pass indices to the kernel that are out of bounds. Adding the conditional doesn't seem to affect performance, which makes sense, since all threads in a block (except the last one) would follow the true branch.

@williamfgc
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Thanks @PhilipFackler eventually we will revisit this when doing performance testing, with the apps we are targeting.

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Test this please

williamfgc
williamfgc approved these changes Apr 18, 2024
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ext/JACCCUDA/JACCCUDA.jl
maxPossibleThreads = CUDA.maxthreads(parallel_kernel)
threads = min(N, maxPossibleThreads)
blocks = ceil(Int, N / threads)
parallel_kernel(parallel_kargs...; threads=threads, blocks=blocks)
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Is this guarantee to be synchronized?

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I don't know :)

@williamfgc
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Also, are we missing the same for AMDGPU.jl?

@williamfgc williamfgc merged commit 6a07365 into JuliaORNL:main Apr 18, 2024
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@PhilipFackler
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Also, are we missing the same for AMDGPU.jl?

Yes, but I don't have a way to check that out locally

@PhilipFackler PhilipFackler mentioned this pull request Jun 5, 2024
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@PhilipFackler PhilipFackler mentioned this pull request Nov 1, 2024
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@williamfgc williamfgc williamfgc approved these changes

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@PhilipFackler @williamfgc