AI-coupled HPC Workflows [article]

Shantenu Jha, Vincent R. Pascuzzi, Matteo Turilli
2022 arXiv   pre-print
Increasingly, scientific discovery requires sophisticated and scalable workflows. Workflows have become the "new applications," wherein multi-scale computing campaigns comprise multiple and heterogeneous executable tasks. In particular, the introduction of AI/ML models into the traditional HPC workflows has been an enabler of highly accurate modeling, typically reducing computational needs compared to traditional methods. This chapter discusses various modes of integrating AI/ML models to HPC
more » ... mputations, resulting in diverse types of AI-coupled HPC workflows. The increasing need of coupling AI/ML and HPC across scientific domains is motivated, and then exemplified by a number of production-grade use cases for each mode. We additionally discuss the primary challenges of extreme-scale AI-coupled HPC campaigns -- task heterogeneity, adaptivity, performance -- and several framework and middleware solutions which aim to address them. While both HPC workflow and AI/ML computing paradigms are independently effective, we highlight how their integration, and ultimate convergence, is leading to significant improvements in scientific performance across a range of domains, ultimately resulting in scientific explorations otherwise unattainable.
arXiv:2208.11745v1 fatcat:fr5y2au7jbardjzrbikayz366y