triton-lang

What problem does it solve?

This Skill allows for the creation of high-performance GPU kernels using a high-level Python syntax, filling the gap between low-level CUDA programming and high-level libraries.

Core Features & Use Cases

• High-Level Programming: Simplifies GPU kernel development with a Python-like syntax.
• Custom Operations: Enables the implementation of custom fused kernels, attention variants, and quantized operations.
• Performance: Achieves optimal performance through automatic scheduling, memory coalescing, and tensor core utilization.
• Use Case: When you need to implement custom operations in deep learning that are not available in existing libraries, such as fused attention or quantized matrix multiplications.

Quick Start

Write a Python function with the @triton.jit decorator and compile it to GPU code.