Workshops Archive

Invited Talk: Scalable Deep Learning Algorithms for Scientific Applications on Leadership Class Computing Systems

Workshop: Workshop on Latest Advances in Scalable Algorithms for Large-Scale Heterogeneous Systems (ScalAH'22)

Authors: Brian Van Essen (Lawrence Livermore National Laboratory)

Abstract: In this talk, we will discuss the challenges and opportunities for implementing deep learning algorithms at scale for scientific applications on leadership class HPC systems. Using examples drawn from multiple application areas we will see how challenges created by algorithmic complexity as well as multiple aspects of large data lend themselves to parallelization schemes. Additionally, we will explore what are the implications and demands for existing and upcoming AI accelerators.

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