commit | 368db7123bf3178c92c8502696c6865fb07bfcda | [log] [tgz] |
---|---|---|
author | Petr Hosek <phosek@google.com> | Thu May 26 09:54:57 2022 -0700 |
committer | Copybara-Service <copybara-worker@google.com> | Thu May 26 09:55:35 2022 -0700 |
tree | c49bf1c4fea21dc58ca6f45dd040c451c9cef41e | |
parent | cd19e0e1b0fd24cd3d785beff1b50583e572dae0 [diff] |
Define namespace prefixed aliases for targets in the CMake build This allows projects that depend on ruy to use namespace qualified target names regardless of whether they consume ruy through add_subdirectory or find_package. Closes https://github.com/google/ruy/pull/311 COPYBARA_INTEGRATE_REVIEW=https://github.com/google/ruy/pull/311 from petrhosek:cmake-alias c00fae2a56a567b216dea0b0fe7378c28ddadbbf PiperOrigin-RevId: 451184466
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.