commit | a4306950c00111804967adf6b636b8146b991395 | [log] [tgz] |
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author | Max191 <44243577+Max191@users.noreply.github.com> | Wed Jan 22 09:57:10 2025 -0500 |
committer | GitHub <noreply@github.com> | Wed Jan 22 06:57:10 2025 -0800 |
tree | 1fdf6e5992a14aa0ea58731c05b2116e3a46870a | |
parent | ba30557d40a15bc8f8ee1fe282eb98d2e7bfc377 [diff] |
[GPU] Add pattern to fuse tensor.collapse_shape into forall producer (#19295) This PR adds a pattern to fuse a consumer tensor.collapse_shape into a producer scf.forall op. The transform is added to FuseAndHoistParallelLoops, where it helps to fuse tensor.unpack ops with extract_slice semantics into producer loops. This is needed when targeting MFMA intrinsics for unaligned shapes, and also in generating code for unset encoding ops on GPU. The PR also adds a transform op to keep the long lit tests separate from the FuseAndHoistParallelLoop tests. Signed-off-by: Max Dawkins <max.dawkins@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.
Releases notes are published on GitHub releases.
Package | Release status |
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GitHub release (stable) | |
GitHub release (nightly) | |
Python iree-base-compiler | |
Python iree-base-runtime |
Operating system | Build status |
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Linux | |
macOS | |
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
Date | Title | Recording | Slides |
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2021-06-09 | IREE Runtime Design Tech Talk | recording | slides |
2020-08-20 | IREE CodeGen (MLIR Open Design Meeting) | recording | slides |
2020-03-18 | Interactive HAL IR Walkthrough | recording | |
2020-01-31 | End-to-end MLIR Workflow in IREE (MLIR Open Design Meeting) | recording | slides |
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.