[CANN]:Replace aclrtMemsetSync with InplaceZero operator for zero tensor creation #14002
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Thanks for your contribute! |
hipudding
requested changes
Jun 9, 2025
ggml/src/ggml-cann/aclnn_ops.cpp
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| @@ -834,6 +837,7 @@ static aclTensor* aclnn_values(ggml_backend_cann_context& ctx, void* buffer, | |||
| float value = 1.0f) { | |||
| aclTensor* acl_tensor = | |||
| aclnn_zero(ctx, buffer, n_bytes, ne, dims, type, type_size); | |||
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Revert this change if unnecessary.
ggml/src/ggml-cann/aclnn_ops.cpp
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| @@ -67,6 +67,7 @@ | |||
| #include <aclnnop/aclnn_pow.h> | |||
| #include <aclnnop/aclnn_grouped_matmul_v2.h> | |||
| #include <aclnnop/aclnn_fused_infer_attention_score_v2.h> | |||
| #include "aclnnop/aclnn_zero.h" | |||
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#include <aclnnop/aclnn_zero.h>
hipudding
reviewed
Jun 9, 2025
ggml/src/ggml-cann/aclnn_ops.cpp
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| aclTensor* zero = | ||
| ggml_cann_create_tensor(buffer, type, type_size, ne, nb, dims); | ||
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unused parameter ‘n_bytes’
Thanks for your feedback! I've corrected the formatting issues as suggested and updated the PR accordingly. Please have a look when you get a chance. |
hipudding
approved these changes
Jun 17, 2025
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Please rebase for CI update. |
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…te zero tensors more efficiently and consistently within the computation graph
I’ve rebased the PR onto the latest main branch to include recent CI-related changes. Could you please help retrigger the CI checks? Thanks! |
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In performance tests on the Atlas 300V NPU, we observed that the aclrtMemsetSync operation introduced significant latency when creating zero tensors.
To address this, we replaced aclrtMemsetSync with the InplaceZero operator. This change allows zero tensors to be created more efficiently and consistently within the computation graph, avoiding costly synchronization and improving execution performance.
This also helps ensure better integration with graph-level optimizations and memory management.
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