Workshop:PMBS20: The 11th International Workshop on Performance Modeling, Benchmarking and Simulation of High-Performance Computer Systems
Authors: Hartwig Anzt and Yuhsiang M. Tsai (Karlsruhe Institute of Technology); Ahmad Abdelfattah (University of Tennessee); Terry Cojean (Karlsruhe Institute of Technology); and Jack Dongarra (University of Tennessee, Oak Ridge National Laboratory)
Abstract: GPU accelerators have become an important backbone for scientific high performance-computing, and the performance advances obtained from adopting new GPU hardware are significant. In this paper, we take a first look at NVIDIA's newest server-line GPU, the A100 architecture, part of the Ampere generation. Specifically, we assess its performance for sparse and batch computations, as these routines are relied upon in many scientific applications, and compare to the performance achieved on NVIDIA's previous server-line GPU.