Publication
ScalA 2015
Conference paper

A scalable randomized least squares solver for dense overdetermined systems

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Abstract

We present a fast randomized least-squares solver for distributedmemory platforms. Our solver is based on the Blendenpik algorithm, but employs a batchwise randomized unitary transformation scheme. The batchwise transformation enables our algorithm to scale the distributed memory vanilla implementation of Blendenpik by up to×3 and provides up to×7.5 speedup over a state-of-the-art scalable least-squares solver based on the classic QR based algorithm. Experimental evaluations on terabyte scale matrices demonstrate excellent speedups on up to 16384 cores on a Blue Gene/Q supercomputer.

Date

15 Nov 2015

Publication

ScalA 2015

Authors

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