Energy footprint of advanced dense numerical linear algebra using tile algorithms on multicore architectures

Jack Dongarra, Hatem Ltaief, Piotr R. Luszczek, Vincent M. Weaver

Research output: Chapter in Book/Report/Conference proceedingConference contribution

39 Scopus citations

Abstract

We propose to study the impact on the energy footprint of two advanced algorithmic strategies in the context of high performance dense linear algebra libraries: (1) mixed precision algorithms with iterative refinement allow to run at the peak performance of single precision floating-point arithmetic while achieving double precision accuracy and (2) tree reduction technique exposes more parallelism when factorizing tall and skinny matrices for solving over determined systems of linear equations or calculating the singular value decomposition. Integrated within the PLASMA library using tile algorithms, which will eventually supersede the block algorithms from LAPACK, both strategies further excel in performance in the presence of a dynamic task scheduler while targeting multicore architecture. Energy consumption measurements are reported along with parallel performance numbers on a dual-socket quad-core Intel Xeon as well as a quad-socket quad-core Intel Sandy Bridge chip, both providing component-based energy monitoring at all levels of the system, through the Power Pack framework and the Running Average Power Limit model, respectively. © 2012 IEEE.
Original languageEnglish (US)
Title of host publication2012 Second International Conference on Cloud and Green Computing
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages274-281
Number of pages8
ISBN (Print)9780769548647
DOIs
StatePublished - Nov 2012

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