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GPU Parallel Programming By Examples - The Bandwidth of Parallel Computing

Schedule and Place


Materials for Coding Session



This is a tutoring plus practice event for parallel programming on GPU. It’s entry-level for programmers with Python experiences. We will work under Google Colab environment, therefore no self-owned GPU hardware is required for participation.

Understanding C/C++ is better but not required. There will be optional activities of implementing the two examples above purely in CUDA C for participants who are willing to dive deeper. A self-owned GPU is required for this practice.

A brief introduction of how the tech stack evolves into the AI era will be a warm-up from the beginning, followed by some essential concepts of GPU parallel programming that are quite different from single thread programming.

We are looking forward to your participation and let’s learn by coding!


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