Practical GPU Programming with Triton for PyTorch Developers

PyTorch Conference North America 2026

Oct 20, 2026 · 11:45–12:10 · Timezone not confirmed

If you've used PyTorch, you've already run thousands of GPU kernels, you just never had to write one. Tools like torch.compile and Triton handle that for you. But what's actually happening underneath, and what if you wanted to write a kernel yourself? This talk is a friendly introduction to GPU programming with Triton, an open-source tool for writing fast GPU code directly in Python, no CUDA, no C++ required. We'll start from the basics: what a GPU kernel is, why GPUs are fast, and how PyTorch quietly generates kernels for you behind the scenes. From there, we'll write our first Triton kernel together, starting with something simple like adding two vectors, then building up to a small matrix multiplication. Along the way you'll pick up the core ideas, how a GPU moves data around, what it means to run thousands of threads at once, and how to check whether your kernel is actually fast; all through plain, readable Python. You'll leave knowing what a GPU kernel really is, how to read the code PyTorch generates for you, and how to write a simple Triton kernel of your own. No prior GPU experience needed, just comfort with Python and PyTorch.

Session status: scheduled

Room: LL20CD

Track: Introduction

Level: Beginner

Official session / agenda

Saving a session is not registration. Check the official agenda for availability, eligibility and any additional fees.

Speakers and their event affiliations

Parent event

In person · San Jose Convention Center, San Jose, California, United States

This describes the parent event. Confirm the session’s attendance requirements with the organizer.

Companies participating in the parent event

These are event-level relationships, not confirmed sponsorship of this session.

Showing 24 of 130 company relationships. View all on the event page.