Session

Description Scientific computing has relied upon commodity components for many years, and currently most popular are x86 CPUs and Nvidia GPUs. However, there is a Cambrian explosion of new types of hardware for accelerating scientific codes and as such a wealth of other options are becoming available. These include extremely high-core count CPUs (e.g. the CS-2 and GraphCore), highly vectorised and flexible processing elements (e.g. AMD’s AI engines, Google TPUs), Field Programmable Gate Arrays (FPGAs) and a range of technologies built upon RISC-V (e.g. the 1000 core Esperanto accelerator). Furthermore, many of these new architectures are capable of being highly energy efficient and-so potentially provide a route to delivering improved performance at reduced environmental cost. However, a major challenge is around how scientific application developers can leverage these technologies, and whether they actually deliver the benefits that the vendors claim. This minisymposium will bring together experts in developing these novel technologies and leveraging them for HPC application acceleration, with the scientific community. We will explore the potential benefits of these new architectures, which ones optimally suit what application properties, and discuss some of the challenges that must be overcome for them to become mainstream in scientific computing.