commit | a400cde96289706512ac873591a9711c81edc244 | [log] [tgz] |
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author | Nirvedh Meshram <96096277+nirvedhmeshram@users.noreply.github.com> | Wed Oct 23 15:34:20 2024 -0500 |
committer | GitHub <noreply@github.com> | Wed Oct 23 15:34:20 2024 -0500 |
tree | 9c885fa50192b7b6dc90ec4afa19d4bdbabb90af | |
parent | 563b3e73c126a56dcabc8d2b17bf6a27347e37ff [diff] |
[ROCM][NFC] Add option to control SLP vectorization in llvm optimizations (#18865) We keep SLP vectorization off because it can mask perf issues or create regressions. However, on ROCM what we have noticed is that we are hitting issues in several untested paths in the AMDGPU llvm backend because we dont have SLP vectorization. Here is an example of an issue that we wouldn't hit if SLP vectorization was turned on https://github.com/iree-org/iree/issues/18798 In this PR we are still keeping the exisiting behavior but provide a flag to toggle it so that we can do the required benchmarking and analysis. Signed-off-by: Nirvedh <nirvedh@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
Package | Release status |
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GitHub release (stable) | |
GitHub release (nightly) | |
Python iree-compiler | |
Python iree-runtime |
Host platform | Build status |
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Linux | |
macOS | |
Windows |
For the full list of workflows see https://iree.dev/developers/general/github-actions/.
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.