commit | 7813fd333a8bc51dfb4f16d0ee0e7429022a150d | [log] [tgz] |
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author | Han-Chung Wang <hanhan0912@gmail.com> | Tue May 21 12:37:32 2024 -0700 |
committer | GitHub <noreply@github.com> | Tue May 21 19:37:32 2024 +0000 |
tree | f29a2b18a798303f753fda16ba143641a42e2233 | |
parent | d4aa8491a755e31d590f00a507e6c3859dfa662d [diff] |
[CPU] Fix a distribution bug and limiting distribution tile sizes. (#17436) The revision adds max limit of each dimension for pack/unpack/reduction ops. This prevents the huge workload being distributed to a worker. So we will have more reasonable performance even we don't know the number of threads on target hardware. The bug is in the distribution heuristics. The target size is too small, which could lead it only distributing to two workers. Since we will reduce the number of workgroups at the end, based on `clNumberOfRuntimeThreads`, we can divide the target size with `clNumberOfRuntimeThreads`, and rely on latter heuristics to fix it up. Signed-off-by: hanhanW <hanhan0912@gmail.com>
IREE (Intermediate Representation Execution Environment, pronounced as “eerie”) is an MLIR-based end-to-end compiler and runtime that lowers Machine Learning (ML) models to a unified IR that scales up to meet the needs of the datacenter and down to satisfy the constraints and special considerations of mobile and edge deployments.
See our website for project details, user guides, and instructions on building from source.
IREE is still in its early phase. We have settled down on the overarching infrastructure and are actively improving various software components as well as project logistics. It is still quite far from ready for everyday use and is made available without any support at the moment. With that said, we welcome any kind of feedback on any communication channels!
See our website for more information.
Community meeting recordings: IREE YouTube channel
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.