triton windows builds

Introduction
This repository provides Windows builds of Triton, a highly efficient and flexible deep learning framework. It includes packages for different versions of Python, facilitating the deployment of Triton on Windows platforms.

Architecture
Triton is designed to optimize deep learning operations and is compatible with CUDA-enabled GPUs. These builds are based on the latest releases from the Triton project hosted on GitHub, ensuring users have access to up-to-date features and improvements.

Training
The Triton framework supports high-performance training of deep learning models. These Windows builds are tailored to leverage CUDA 12.X, enabling efficient computation on NVIDIA GPUs.

Guide: Running Locally

1. Download the Wheel File: Choose the appropriate Triton package for your Python version from the links provided:

   • For Python 3.10: triton-3.0.0-cp310-cp310-win_amd64.whl
   • For Python 3.11: triton-3.0.0-cp311-cp311-win_amd64.whl
   • For Python 3.12: triton-3.0.0-cp312-cp312-win_amd64.whl

2. Install the Package: Use pip to install the downloaded wheel file.

   pip install triton-3.0.0-cp310-cp310-win_amd64.whl
   

3. Verify Installation: Ensure CUDA 12.X is installed and properly configured on your system.

4. Utilize Cloud GPUs: For large-scale training or enhanced performance, consider using cloud GPU services like AWS, Google Cloud, or Azure.

License
The Triton builds are distributed under the terms specified in the original Triton GitHub repository, adhering to open-source licensing guidelines.