In this lecture, we will look into the basics of GPU computing to understand in which circumstances the usage of GPUs is beneficial for scientific computing. Using the Nvidia CUDA GPUs as examples, will learn how the hardware works, which guides us towards how it has to be programmed.
Students should have written basic C/C++ programs before, and should be familiar with pointers and arrays and/or vectors of data.
Hands on: We have the option to play with a few basic CUDA applications. There's three ways in which you can participate:
Stephan obtained a PhD in particle physics, searching for decays of the Higgs boson with the ATLAS detector. Afterwards, he worked for the ROOT project at CERN, focussing on high-throughput computing and RooFit, a package for fitting and statistical analysis of data. Now, Stephan is a computing engineer in CERN IT's innovation group, focussing on GPU computing for high-energy physics.