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update OneMKL gemm_batch call inside dpnp.matmul and column_major version of gemm
#1793
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View rendered docs @ https://intelpython.github.io/dpnp/pull//index.html |
antonwolfy
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This is a great improvement. Thank you @vtavana !
split batch_size to smaller chunks and gemm with column major when both input array F-contig
gemm_batch call inside dpnp.matmulgemm_batch call inside dpnp.matmul and column_major version of gemm
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…eep their alphabetic order
antonwolfy
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Thank you @vtavana , no more comments from me
In this PR,
oneapi::mkl::blas::column_major::gemmandoneapi::mkl::blas::column_major::gemm_batchare added to be used indpnp.matmulwhen the base of input arrays is f-contiguous.In addition, the
gemm_batchis updated to improve the performance for some cases by keeping the base of intermediate arrays the same as input arrays (working with arrays views instead of copying).Also, for large values of
batch_sizeingemm_batch, thebatch_sizeis split to smaller chunk sizes to avoid OneMKL error.