GPU Coding Using Triton Compiler | AI with Guy

Published on 6 Jun 2025, 15:21

Avoid the complexity of CUDA and lower-level languages with the Triton compiler running on Intel GPUs. In this video, we show how to get started with Triton using Intel’s backend—making GPU programming more accessible, flexible, and portable.

You’ll see just how fast it is to launch a Jupyter Notebook, start programming, and run high-performance kernels on Intel GPUs—without writing device-specific code. This setup is ideal for developers and researchers looking to simplify their AI, ML, and HPC workloads.

What you’ll learn:
– How to run Triton with Intel’s open-source backend
– How to set up your development environment with Jupyter
– How Triton compares to CUDA for writing custom GPU kernels
– Where Triton fits in modern AI workflows using Intel GPUs

Resources:
GitHub: github.com/intel/intel-xpu-bac...
Intel Cloud Optimization Hub: cloud.intel.com

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How to Use Triton Compiler on Intel GPUs | AI with Guy | Intel Software