Triton
Triton is an open-source programming language and compiler developed by OpenAI for writing highly efficient GPU kernels, particularly for AI/ML workloads. It allows developers to write CUDA-like code in Python that gets compiled to optimized GPU instructions, making it easier to create custom operations for deep learning frameworks.
AI companies need to optimize model inference and training performance on specialized hardware like GPUs and TPUs, and Triton provides a more accessible way to write high-performance kernels than raw CUDA. As models grow larger and more complex, the ability to create custom, efficient operations becomes critical for competitive advantage in deployment.
🎓 Courses
Triton: An Intermediate Representation and Compiler for Tiled Neural Network Computations
by Philippe Tillet
This presentation by Triton's creator explains the core concepts and design philosophy behind the language.
GPU Programming with Triton
by Sasha Rush
A practical tutorial showing how to write and optimize GPU kernels using Triton with concrete examples.
Triton Tutorial - OpenAI's GPU Programming Language
by Various
Hands-on walkthrough of Triton's syntax and features for writing efficient GPU kernels.
📖 Books
Programming Massively Parallel Processors: A Hands-on Approach
David B. Kirk, Wen-mei W. Hwu · 2023
While not Triton-specific, this updated edition provides essential GPU programming concepts that underpin Triton's approach.
🛠️ Tutorials & Guides
OpenAI Triton Tutorial
The official repository with examples, documentation, and getting started guides for Triton.
Getting Started with Triton
Official PyTorch tutorial showing how to integrate Triton kernels with PyTorch models.
Triton: GPU Programming for ML Researchers
Practical guide to using Triton for optimizing transformer models and custom operations.
Writing Efficient GPU Kernels with Triton
Step-by-step tutorial on creating and benchmarking Triton kernels for common ML operations.
Learning resources last updated: April 14, 2026