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Allow 0-stride dimensions for cublas input/output #400
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Currently, if a tensor contains 0-stride dimensions in one of the last two dimensions, then that tensor will not be used directly as input/output to cublas and a copy will be made transparently. This generates copies during matvec operations because matvec clones a tensor and delegates to matmul, which then copies the tensor because the clone creates a 0-stride dimension. This change allows 0-stride dimensions if the dimension size is 1 (and thus no index will stride in that dimension) and thus eliminates allocations/frees and copies when calling matvec.
luitjens
approved these changes
Mar 30, 2023
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thanks for adding all the tests! |
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tylera-nvidia
approved these changes
Mar 31, 2023
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4 similar comments
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Currently, if a tensor contains 0-stride dimensions in one of the last two dimensions, then that tensor will not be used directly as input/output to cublas matmul and a copy will be made transparently. This generates copies during matvec operations because matvec clones a tensor and delegates to matmul, which then copies the tensor because the clone creates a 0-stride dimension. This change allows 0-stride dimensions if the dimension size is 1 (and thus no index will stride in that dimension) and thus eliminates allocations/frees and copies when calling matvec.