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CUDA/HIP: refractor mmqv to unify the calculation of nwarps and rows per block between host and device code. #12177
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…between host and device code.
…s in device code, even though that should not be a problem.
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Please use an enum instead of an int to determine the table.
JohannesGaessler
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Mar 7, 2025
Co-authored-by: Johannes Gäßler <[email protected]>
ishaangandhi
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Mar 12, 2025
…per block between host and device code. (ggml-org#12177) refactor mmqv to unify the calculation of nwarps and rows per block between host and device code. --------- Co-authored-by: Johannes Gäßler <[email protected]>
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Mar 14, 2025
…per block between host and device code. (ggml-org#12177) refactor mmqv to unify the calculation of nwarps and rows per block between host and device code. --------- Co-authored-by: Johannes Gäßler <[email protected]>
arthw
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Mar 19, 2025
…per block between host and device code. (ggml-org#12177) refactor mmqv to unify the calculation of nwarps and rows per block between host and device code. --------- Co-authored-by: Johannes Gäßler <[email protected]>
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ggml
changes relating to the ggml tensor library for machine learning
Nvidia GPU
Issues specific to Nvidia GPUs
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This refactors mmqv to unify the handling of parameters between host and device side code, avoideing duplication in calculateing nwarps and rows_per_cuda_block. Also explicitly handles wave_size != 32, for the minor benefit of getting us out of shared memory into warp level primitives one iteration earlier.