Conference Keynote: Beyond Exascale Computing

The first generation of exascale computing systems are online, with powerful new application capabilities and system software. At the same time, demands for high performance computing continue to grow for more powerful simulations, adoption of machine learning methods, and huge data analysis problems arising for new instruments and increasingly ubiquitous data collection devices. In its broadest sense, computational science research is expanding beyond physical and life sciences into social sciences, public policy, and even the humanities. With chip technology facing scaling limits and diminishing benefits of weak scaling, it will be increasingly difficult to meet these new demands. Disruptions in the computing marketplace, which include supply chain limitations, a shrinking set of system integrators, and the growing influence of cloud providers are changing underlying assumptions about how to acquire and deploy future supercomputers. At the same time there are discussions around cloud computing, specialized hardware, and the role of AI, both as a technique in science and as a driver of computing hardware and software. In this talk I’ll present some of the findings of a US National Academies consensus report on the future of post-exascale computing, which states that business as usual will not be sufficient. I will also give my own perspectives on some of the challenges and opportunities faced by the research community.