Experience From Ginkgo Porting to the SYCL Ecosystem
DescriptionIntel has introduced new GPU architectures into the High-Performance Computing markets and has chosen the SYCL ecosystem for its devices. Based on SYCL, they create several extensions to help the coding experience and improve usability. They also provide the tools to help port the code from CUDA and measure the performance. Many applications rely on mathematical libraries, so mathematical libraries need to be available on these new devices. With the new Exascale machine Aurora using Intel GPU accelerators, Ginkgo, which is a sparse linear algebra library, also faces the challenge of porting the code to the new Intel GPUs. Moreover, Ginkgo needs to provide competitive performance and good portability. We show the ginkgo portability design such that we can add SYCL to our structure. We also share the challenges, concerns, and experiences from porting Ginkgo to SYCL. In the end, we summarize the supported functionality on different GPUs from different vendors.
TimeTuesday, June 2712:00 - 12:30 CEST
Computer Science, Machine Learning, and Applied Mathematics