Session

DescriptionHPC and data-intensive computing now stand as the fourth pillar of science. The integration of machine learning, AI, and HPC techniques, combined with the availability of massive amounts of compute resources, holds the promise of revolutionizing scientific computing. However, while fast moving technologies promise many exciting possibilities, they also bring drawbacks and risks. One such risk is proprietary tools, walled gardens of vendor libraries and APIs. Scientific communities require standards-based, portable, and interoperable tools to program computing systems—from edge to HPC data center to cloud—to achieve the goal of efficiently combining physics-based simulations with novel machine learning and AI based methods. SYCL promises to be such a tool, offering interoperability and avoiding vendor lock-in, highlighted by it being the cornerstone technology of the SYCLOPS project for development of an open ecosystem for AI acceleration. SYCL is a high-level, vendor-agnostic standard for heterogeneous computing with several mature implementations targeting a wide range of hardware accelerators. It has been adopted by several large HPC projects as their performance-portability layer. This minisymposium aims to discuss SYCL primarily from the perspective of scientific application developers, sharing the experiences and promoting interdisciplinary communication in software engineering for modern, performance-portable, and maintainable code.