@conference {tsai2023mixed,
	title = {Mixed Precision Algebraic Multigrid on {GPUs}},
	booktitle = { Parallel Processing and Applied Mathematics (PPAM 2022)},
	volume = {13826},
	year = {2023},
	month = {2023-04},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {In this paper, we present the first GPU-native platform-portable algebraic multigrid (AMG) implementation that allows the user to use different precision formats for the distinct multigrid levels. The AMG we present uses an aggregation size 2 parallel graph match as the AMG coarsening strategy. The implementation provides a high level of flexibility in terms of configuring the bottom-level solver and the precision format for the distinct levels. We present convergence and performance results on the GPUs from AMD, Intel, and NVIDIA, and compare against corresponding functionality available in other libraries.},
	keywords = {Algebraic multigrid, GPUs, mixed precision, Portability},
	isbn = {978-3-031-30441-5},
	doi = {10.1007/978-3-031-30442-2_9},
	url = {https://link.springer.com/10.1007/978-3-031-30442-2},
	author = {Tsai, Yu-Hsiang Mike and Natalie Beams and Anzt, Hartwig},
	editor = {Wyrzykowski, Roman and Dongarra, Jack and Deelman, Ewa and Karczewski, Konrad}
}
