The PyTorch ATX Triton event, sponsored by Red Hat, was held on April 30, 2025, at the University of Texas. It was an exciting gathering focused on the Triton framework and its role in optimizing and democratizing GPU performance. A key purpose of the event was to highlight the awesome Triton contributors based in Austin and working for companies like Red Hat, Intel, AMD, IBM Research, and the University of Texas. Bringing contributors together helped to share insights and foster a stronger community.
More than 50 attendees gathered to hear experts from these organizations discuss the growing importance of Triton in optimizing GPU efficiency for various algorithms. Key topics included understanding how to write, optimize, and troubleshoot Triton kernels to maximize GPU utilization and kernel portability.
Presentations covered a range of subjects from an introduction to Triton and its significance in vendor-neutral hardware acceleration, new sub-projects exploring increased developer productivity and runtime performance, to specific use cases such as Triton for vLLM and the Triton implementations by AMD and Intel. All session videos can be found here (YouTube). Speakers also examined the Triton framework itself, along with its release process, providing attendees with a comprehensive overview of the technology and its application.
This event aimed to equip the PyTorch ATX community with the knowledge and skills necessary to leverage Triton effectively and foster a deeper understanding of Triton’s capabilities by introducing and connecting local contributors. And guess what? This event worked out so well that we’re going to be hosting another large PyTorch ATX event focused on vLLM and the future of inferencing, coming up in August! Sign up here.