commit | 998a6df5933c918fe486c3cbd3cb1e699e0211b5 | [log] [tgz] |
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author | Lev Proleev <levp@google.com> | Fri Mar 12 18:40:35 2021 +0000 |
committer | Automerger Merge Worker <android-build-automerger-merge-worker@system.gserviceaccount.com> | Fri Mar 12 18:40:35 2021 +0000 |
tree | 45b033783360ed59b9efbfd8bd2dfdb4fc8bdb72 | |
parent | d23d5384ee2dad29223e8c57248ea83ec23da4bf [diff] | |
parent | 039d972c6ee12b3bd9c692b061060f8b398b40fe [diff] |
Merge remote-tracking branch 'aosp/upstream-master' into tflite-rebase-feb-2021 am: 713d254ecf am: dd1f1778c2 am: 039d972c6e Original change: https://android-review.googlesource.com/c/platform/external/ruy/+/1610773 MUST ONLY BE SUBMITTED BY AUTOMERGER Change-Id: I79d6492983ed7da9b99eae3df035ac69eb3c5b65
This is not an officially supported Google product.
ruy is a matrix multiplication library. Its focus is to cover the matrix multiplication needs of neural network inference engines. Its initial user has been TensorFlow Lite, where it is used by default on the ARM CPU architecture.
ruy supports both floating-point and 8bit-integer-quantized matrices.
ruy is designed to achieve high performance not just on very large sizes, as is the focus of many established libraries, but on whatever are the actual sizes and shapes of matrices most critical in current TensorFlow Lite applications. This often means quite small sizes, e.g. 100x100 or even 50x50, and all sorts of rectangular shapes. It's not as fast as completely specialized code for each shape, but it aims to offer a good compromise of speed across all shapes and a small binary size.
Some documentation will eventually be available in the doc/ directory, see doc/README.md.