Enable Direct Use of Arm Compute Library (ACL) in ATen #148542
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ACL is already built with PyTorch as a shared library when USE_MKLDNN_ACL is set. Currently, it is only used indirectly in ATen via oneDNN for AArch64 targets. However there are cases where it makes sense to utilize ACL directly without oneDNN as an intermediary - e.g. quantization. See pytorch#145942, pytorch#147337, pytorch#146620. This patch enables such use cases by exposing ACL to ATen
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/148542
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 99e5d35 with merge base 6c3492b ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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@pytorchbot label "module: arm" |
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@pytorchbot label "ciflow/linux-aarch64" |
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@pytorchbot label "topic: not user facing" |
This was referenced Mar 5, 2025
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@malfet, @digantdesai This PR contains all the cmake-related changes needed to enable the direct ACL path in ATen in these PRs: #145942, #147337, #146620. |
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@pytorchbot label "arm priority" |
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ACL is already built with PyTorch as a shared library when USE_MKLDNN_ACL is set.
Currently, it is only used indirectly in ATen via oneDNN for AArch64 targets. However there are cases where it makes sense to utilize ACL directly without oneDNN as an intermediary - e.g. quantization. See #145942, #147337, #146620.
This patch enables such use cases by exposing ACL to ATen
Fixes #ISSUE_NUMBER
cc @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10 @malfet @snadampal @milpuz01