commit | 772c47bf8d4b156d0b3924e1cc2d9994b1bdadd9 | [log] [tgz] |
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author | Han-Chung Wang <hanchung@google.com> | Wed Aug 04 01:48:54 2021 +0800 |
committer | GitHub <noreply@github.com> | Tue Aug 03 10:48:54 2021 -0700 |
tree | 372d90a15292caabfea8c2b99d6e6045c6f0f2ea | |
parent | a2dc67da4fe4b09b4a18bf7bfca2aa36906af8fe [diff] |
Add support for lowering mhlo.fft to linalg_ext.fft (#6602) This is a new path which lowers the op to linalg_ext. The old pipeline is through DFT implementation, ie matmul. This improves the RFFT kernel (tensor<325x1024xf32>) from 33 ms to 14.5 ms (single-threaded), even the kernel is serialized. The next step is to implement tiling method and we can get more performance improvements. This is a step toward https://github.com/google/iree/issues/6477
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.