Democratizing AI Accelerators for HPC Applications:
Challenges, Success, and Support

Welcome

A recent surge in novel AI accelerator hardware (e.g. from Cerebras, Groq, SambaNova, Graphcore, Intel, and Tenstorrent) has sparked intense interest in running HPC applications and driven algorithmic research on these architectures. However, the maturity levels of associated tooling and software stacks vary significantly, with gaps in documentation and support. This BoF aims to explore trends in AI accelerators for HPC, ideal programming models, software stack support, code portability, training resources, and common challenges. We hope to foster a community of users interested or experienced in using AI accelerators for HPC applications.

Organizers

Murali Emani, Argonne National Laboratory (ANL)

Siddhisanket Raskar, Argonne National Laboratory (ANL)

Tal Ben-Nun, Lawrence Livermore National Laboratory (LLNL)

Brian Van Essen, Lawrence Livermore National Laboratory (LLNL)

Hatem Ltaief, King Abdullah University of Science & Technology (KAUST)