Computer Science, Machine Learning, and Applied Mathematics
TimeTuesday, June 2716:00 - 18:00 CEST
DescriptionAccelerators, namely GPUs, have become the workhorse for floating-point/high-bandwidth intensive applications. Software development efforts in this domain have originally been focused around the CUDA programming model tailored for NVIDIA GPUs. In 2016 AMD introduced the HIP Programming language, a C++ runtime API and kernel language that allows developers to create portable applications. Several projects for porting scientific libraries and applications to run on AMD GPUs have started with many large supercomputers equipped with AMD GPUs in several supercomputer centers (e.g. Frontier in the USA and LUMI in Finland) entering production. Moreover, AMD has led a substantial effort to develop a comprehensive ecosystem for AMD GPUs, including compilers, profiling, and debugging tools. For supercomputers provided by HPE, the HPE Cray Programming Environment also offers tools for compilation and profiling as well as optimized libraries for fast MPI GPU-aware communications and most notably an OpenACC implementation for AMD GPUs. The goal of the minisymposium is to gather researchers and developers to discuss their experiences with application development and porting to AMD GPU devices.