| commit | 4c9cb3c336678fd8a6243da051dcf5ec617cc928 | [log] [tgz] |
|---|---|---|
| author | Quinn Dawkins <quinn.dawkins@gmail.com> | Tue May 07 06:29:37 2024 -0700 |
| committer | GitHub <noreply@github.com> | Tue May 07 13:29:37 2024 +0000 |
| tree | a9038ab39c66e20825801bba50819f8b81a7f796 | |
| parent | 098b0c4e89c84283e12ac02fadf27be479bcc892 [diff] |
[Codegen] Add iree_gpu.shuffle_tensor op (#17257) This adds an operation for shuffling tensors when fusing two parallel loops together with tensor results. The `iree_gpu.shuffle_tensor` op can be thought of generally as a `tensor.insert_slice` from the source tensor to an intermediate allocation, and then a `tensor.extract_slice` from that intermediate allocation. This can be broken down directly into a sequence of vector transfer ops and a `memref.alloc`, however having the operation allows a more gradual lowering and better control in the future when considering transformations like pipelining by not having to jump straight to memrefs + barriers. This just adds the op structure. Patterns for lowering and generating this operation will be added in subsequent patches.
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.