This PR; - Fixes syntax errors like `.type values: dict[str, Callable[[list[Any]], Any]]` to `:type values: dict[str, Callable[[list[Any]], Any]]`, - Fixes typos, - Fixes formatting like `k ++` to ` k++`, - Increases consistency (e.g. by transforming the minority `cd dir/` to the majority `cd dir`).
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Triton
This is the development repository of Triton, a language and compiler for writing highly efficient custom Deep-Learning primitives. The aim of Triton is to provide an open-source environment to write fast code at higher productivity than CUDA, but also with higher flexibility than other existing DSLs.
The foundations of this project are described in the following MAPL2019 publication: Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations. Please consider citing this work if you use Triton!
The official documentation contains installation instructions and tutorials.
Quick Installation
You can install the latest stable release of Triton from pip:
pip install triton
Binary wheels are available for CPython 3.6-3.11 and PyPy 3.7-3.9.
And the latest nightly release:
pip install -U --pre triton
Install from source
git clone https://github.com/openai/triton.git;
cd triton/python;
pip install cmake; # build-time dependency
pip install -e .
Changelog
Version 2.0 is out! New features include:
- Many, many bug fixes
- Performance improvements
- Backend rewritten to use MLIR
- Support for kernels that contain back-to-back matmuls (e.g., flash attention)
Contributing
Community contributions are more than welcome, whether it be to fix bugs or to add new features. Feel free to open GitHub issues about your contribution ideas, and we will review them. Please do not submit PRs that simply fix simple typos in our documentation -- unless they can lead to confusion.
Note 1: A more detailed contributor's guide containing general guidelines is coming soon!
Note 2: If you’re interested in joining our team and working on Triton & GPU kernels, we’re hiring!
Compatibility
Supported Platforms:
- Linux
Supported Hardware:
- NVIDIA GPUs (Compute Capability 7.0+)
- Under development: AMD GPUs, CPUs
