8 Feb 2022
9 Feb 2022
This workshop introduces the fundamental knowledge needed to start programming GPUs using Python and CUDA.
From deep learning to high-performance computing, Graphics Processing Units (GPUs) are nowadays an important tool for scholars and research software engineers alike. Parallel in nature, they offer incredible computing capabilities that just a few years ago were only available in supercomputers. While using GPUs to accelerate computation becomes easier year after year, obtaining high performance from these devices still requires some knowledge of how they work, and the programming model on which they are based.
In this workshop we will provide the learners with the fundamental knowledge that they need to start their journey into the world of programming GPUs. After a brief introduction to the specificities of GPUs, and how they differ from traditional processors, participants will experience various ways of using them with Python. They will get familiar with libraries such as CuPy and Numba to accelerate Python code, and have first-hand experience in writing small CUDA programs that can run directly on the GPU. The workshop is based on the teaching style of the Carpentries, and learners will follow along while the instructors write the code on screen. More information can be found on the workshop website.
This workshop is aimed at PhD candidates and other researchers or research software engineers. You need basic skills in Python (and preferably NumPy), and the ability to read and understand C code, to participate in this workshop. Familiarity with high-performance computing concepts will be helpful but is not necessary.
Tickets for this workshop are sold out.