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[BUG] pairwise distances and fused L2 1-NN kernels is limited by launch config #221
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@teju85 FYI. |
Hello , is there any update on this issue? |
this PR addresses this issue - #232 |
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This PR addresses issues mentioned in #221 -- Adds grid stride based fusedL2NN kernel, this gives approx 1.85x speed up over previous version of this kernel. -- Adds support in pairwise dist base class to work for any input size by adding support for grid stride based work distribution. Authors: - Mahesh Doijade (https://github.com/mdoijade) Approvers: - Thejaswi. N. S (https://github.com/teju85) - Divye Gala (https://github.com/divyegala) - Alex Fender (https://github.com/afender) URL: #232
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This PR addresses issues mentioned in #221 -- Adds grid stride based fusedL2NN kernel, this gives approx 1.85x speed up over previous version of this kernel. -- Adds support in pairwise dist base class to work for any input size by adding support for grid stride based work distribution. This was submitted to branch-21.06 through PR - #232 but later reverted due to intermittent failure by - #246 Authors: - Mahesh Doijade (https://github.com/mdoijade) Approvers: - Thejaswi. N. S (https://github.com/teju85) - Brad Rees (https://github.com/BradReesWork) URL: #250
closing this issue as the fix PR is merged now in branch-21.08 . |
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Describe the bug
pairwise distances and fused L2 1-NN kernels which are based on contractions_NT class launches CTAs proportional to the input size.
Due to this it can only launch kernels where number of blocks in
Y
is less than 65536 as this is the max limit of cuda kernel grid size.This severely limits the input size which these kernels can process.
This should be converted to be grid strided kernels launching CTAs based on GPU occupancy heuristics.
Steps/Code to reproduce bug
make the
n
in any of the pairwise distances/fused L2-NN kernel to be of size 65536x64 and run the kernelExpected behavior
A clear and concise description of what you expected to happen.
Environment details (please complete the following information):
docker pull
&docker run
commands usedAdditional context
Add any other context about the problem here.
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