2019/09/30 by Vedran Novaković, Sanja Singer · 1 citation
Mathematics · Computer Science · #math.NA #cs.MS #cs.NA #msc:65F15 #msc:65F25 #msc:65Y05 #msc:65Y10
paper · pdf · doi:10.1177/1094342020972772
published as Int. J. High Perform. Comput. Appl. 35 (2021), 2; 170-205 · A minor revision of the revised submission, with the supplementary material attached
arxiv created 2020/10/13 · arxiv updated 2021/02/18
A parallel, blocked, one-sided Hari--Zimmermann algorithm for the generalized singular value decomposition (GSVD) of a real or a complex matrix pair (F,G) is here proposed, where F and G have the same number of columns, and are both of the full column rank. The algorithm targets either a single graphics processing unit (GPU), or a cluster of those, performs all non-trivial computation exclusively on the GPUs, requires the minimal amount of memory to be reasonably expected, scales acceptably with the increase of the number of GPUs available, and guarantees the reproducible, bitwise identical output of the runs repeated over the same input and with the same number of GPUs.