commit | f8b13d84cabc6094356b1686f5bcc5ab1c22e2f7 | [log] [tgz] |
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author | Han-Chung Wang <hanchung@google.com> | Thu Jul 01 09:33:47 2021 +0800 |
committer | GitHub <noreply@github.com> | Wed Jun 30 18:33:47 2021 -0700 |
tree | d0b20b66cd8d7a3b8b0a743e99662406683fa422 | |
parent | bd1d8a0f55c40fd9670c99be59d727701f067f63 [diff] |
Add support for lowering mhlo.sort to linalg_ext ops and distrubute them (#6360) The pass creates flow.dispatch.workgroups ops and pull the lowered sort op into the body. The workgroup counts are all set to one. Also adds a build method to flow.dispatch.tensor.store and update linalg_ext.sort definition. This is a step towards https://github.com/google/iree/issues/6154
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!
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.