| commit | c200f59184b6d0bda940aadfbaafa957a72f291c | [log] [tgz] |
|---|---|---|
| author | bjacob <jacob.benoit.1@gmail.com> | Wed Jan 20 13:09:30 2021 -0800 |
| committer | Copybara-Service <copybara-worker@google.com> | Wed Jan 20 13:09:50 2021 -0800 |
| tree | 308ec4ee534c5c1e64ab00bc5250898533d81389 | |
| parent | 45a876f72309a444cf01f9cd0e844ac06c520987 [diff] |
Update depgraph - Switch to same colors as in ruy html traces - Move `:thread_pool` to its own yellow color for consistency with ruy traces - Drop `:validate` - Drop the legend, will be redundant in the context of markdown docs showing these different materials in the same context. preview: https://github.com/google/ruy/blob/84dd41f433b3befad6c711248a5d0f00fd8b2711/doc/depgraph.svg Closes https://github.com/google/ruy/pull/241 COPYBARA_INTEGRATE_REVIEW=https://github.com/google/ruy/pull/241 from bjacob:depgraph-update 8f2fa1d9a178c62b80fcc940c9d6ca5cf8ce3c41 PiperOrigin-RevId: 352858626
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.
