Jacob Tomlinson
Summary
Writing GPU code in Python is easier today than ever, and in this tutorial, I will share what I’ve learned and how you can get started with accelerating your code. You don’t need to learn C++ and you don’t need any special tooling. All you need is an NVIDIA GPU, Python and a few libraries (and we’ll provide that for the tutorial).
Description
Writing GPU code in Python is easier today than ever!
I joined NVIDIA in 2019 and I was brand new to GPU development. In that time, I’ve gotten to grips with the fundamentals of writing accelerated code in Python. I was amazed to discover that I didn’t need to learn C++ and I didn’t need new development tools. Writing GPU code in Python is easier today than ever, and in this tutorial, I will share what I’ve learned and how you can get started with accelerating your code.
We will work through various materials and examples to get you started with GPU development in Python using open source libraries.
Tentative schedule:
- Intro to GPUs (20 mins)
- Writing low level GPU code in Python with Numba (30 mins)
- Inspecting your GPU usage with pyNVML (10 mins)
- Writing high level GPU code in Python with RAPIDS (30 mins)
Attendees will be expected to have a general knowledge of Python and programming concepts, but no GPU experience will be necessary. Our key takeaway for attendees will be the knowledge that they don’t have to do much differently to get their code running on a GPU.