Developing for Nvidia GPUs using SYCL with oneAPI
Support from the community for SYCL is growing, with some of the most powerful supercomputers in the world (including Aurora, Perlmutter and Frontier) adopting the programming model for cutting edge research. By migrating your code from CUDA to SYCL it’s not only possible to still target Nvidia GPUs, but it’s also possible to deploy to a wider set of GPUs from different companies including Intel and AMD. This hands-on workshop will introduce the basics of how to set up your development environment to use SYCL to target Nvidia GPUs using oneAPI and what you need to know to migrate your code from CUDA to SYCL. Find out how to use incremental porting by using interoperability for native CUDA kernel code and libraries and learn the fundamentals needed to get the full performance with SYCL. In addition, learn how you can call CUDA libraries such as cuDNN or cuBLAS directly, or via existing SYCL libraries such as oneDNN using oneAPI for CUDA.
Speaker(s)
Joe Todd
Joe Todd is a Senior Software Engineer at Codeplay with a decade of experience developing parallel software. Joe’s career began with a PhD in glaciology at the University of Cambridge, during which he implemented an ice-fracture extension to the parallel finite element model Elmer FEM. Subsequently he spent several years as a post-doctoral researcher at the University of St Andrews & the University of Edinburgh, developing a massively-parallel particle-based fracture model & a Bayesian framework for uncertainty propagation through ice sheet models. Most recently, driven by a desire to focus on software engineering, Joe left academia to join Codeplay, where he works on SYCL’s CUDA backend, with a continuing focus on particle simulators.
