@conference {,
	title = {Evaluating the Performance of NVIDIA{\textquoteright}s A100 Ampere GPU for Sparse and Batched Computations},
	booktitle = {2020 IEEE/ACM Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS)},
	year = {2020},
	month = {2020-11},
	publisher = {IEEE},
	organization = {IEEE},
	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{\textquoteright}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},
	keywords = {Batched linear algebra, NVIDIA A100 GPU, sparse linear algebra, Sparse Matrix Vector Product},
	author = {Hartwig Anzt and Yuhsiang M. Tsai and Ahmad Abdelfattah and Terry Cojean and Jack Dongarra}
}
