Kernel Tuner Tutorial at IEEE eScience 2021


GPU Code Optimization and Auto-tuning Made Easy with Kernel Tuner: A Hands-on, Bring Your Own Code Tutorial

In this tutorial, you will learn how to use Kernel Tuner, an easy-to-use tool for auto-tuning GPU codes using simple Python scripts. Kernel Tuner supports OpenCL, CUDA, C++, and Fortran. We will take a step-by-step approach to explain the auto-tuning basics, such as tuning GPU kernel thread block dimensions, building up to more complex search spaces with many tunable parameters and interdependencies. We will cover a wide range of topics from the basics of GPU code optimization, parameterizing code, and verifying the output of kernels with many different parameterizations, to using advance search space optimization strategies to accelerate the auto-tuning process.

Participants are welcome to bring their own code for the exercises, but we also have plenty of code examples to work with. Experienced GPU programmers will join as mentors to assist participants with using Kernel Tuner on their code. Participants can use Jupyter Notebooks and Google Colab if they don’t have access to a machine with GPUs.

Speakers Ben van Werkhoven, Netherlands eScience Center Alessio Sclocco, Netherlands eScience Center

Registration Participants have to register for the IEEE eScience 2021 conference at: https://www.escience2021.orgregistration (110 euros for non-members)

Time and place Monday, September 20 2021, 9:30 - 16:00 CEST (online event)

Links eScience Conference Kernel Tuner repository