commit | a04c262e54816a3e7d34e76df76510ce6324803e | [log] [tgz] |
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author | Quinn Dawkins <quinn@nod-labs.com> | Wed Feb 15 23:10:51 2023 -0500 |
committer | GitHub <noreply@github.com> | Wed Feb 15 20:10:51 2023 -0800 |
tree | 156b53b4e78274c007a057a73615cb0d660136eb | |
parent | e2dfc65e5a9c916d234ca59f07b7e2a4250299e1 [diff] |
[spirv] Vectorize integer extend ops in lowering to subgroup_mma (#12202) For integer types, integer extend ops are matched against neighboring vector.transfer_read/contract ops when lowering to mma ops. This enables vectorizing the extend ops to cooperative matrix sizes. This also enables support for cases with mixed signedness. Depends on https://reviews.llvm.org/D143922
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.
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.