commit | d65bcd7add7b5e7587355e4301c1b8ce335a877a | [log] [tgz] |
---|---|---|
author | Benoit Jacob <benoitjacob@google.com> | Wed Jan 20 14:04:41 2021 -0800 |
committer | Copybara-Service <copybara-worker@google.com> | Wed Jan 20 14:05:04 2021 -0800 |
tree | e976cfe508a5cbe11dc5d8aecbedadc935ce3b00 | |
parent | c200f59184b6d0bda940aadfbaafa957a72f291c [diff] |
Fixes for builds in open source projects with cpuinfo and googletest deps. - Following XNNPACK's example, in CMakeLists.txt, skip including our own third_party/ directories if the target is already defined. This means that IREE embedding ruy as a third_party/ dep does not need to have its submodules checked out, ruy can use IREE's own cpuinfo and googletest. - Switch open-source builds to using the stripped-include-paths flavor of cpuinfo (like IREE is already using). PiperOrigin-RevId: 352871140
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.