| commit | 3a64294a3f015edd6c594900a4165ae3c8b49d02 | [log] [tgz] |
|---|---|---|
| author | Oleksandr "Alex" Zinenko <zinenko@google.com> | Mon Jul 03 18:30:42 2023 +0200 |
| committer | GitHub <noreply@github.com> | Mon Jul 03 16:30:42 2023 +0000 |
| tree | bd1b7d0b58aecd213bd43c3ed575d64c0923a958 | |
| parent | 6de4a73170e8282220bb1651da92a2e72fa4b7e9 [diff] |
Extend TD strategy to support batched matmul (#14292) Extend the transform dialect strategy for matmul to also support batched matmul. This is guarded by a different flag and is *disabled by default*. The extension maps the batch dimension to blocks/threads along the Z axis. Good default values will come separately after an end-to-end experimentation. Co-authored-by: Nicolas Vasilache <ntv@google.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.
IREE is licensed under the terms of the Apache 2.0 License with LLVM Exceptions. See LICENSE for more information.