Submitted by scrawford on
| Title | Evaluating the Performance of NVIDIA’s A100 Ampere GPU for Sparse and Batched Computations |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Anzt, H., Y. M. Tsai, A. Abdelfattah, T. Cojean, and J. Dongarra |
| Conference Name | 2020 IEEE/ACM Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS) |
| Date Published | 2020-11 |
| Publisher | IEEE |
| Keywords | Batched linear algebra, NVIDIA A100 GPU, sparse linear algebra, Sparse Matrix Vector Product |
| 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 p |
File:
External Publication Flag:
