Profiling high performance dense linear algebra algorithms on multicore architectures for power and energy efficiency

Authors:
Hatem Ltaief;Piotr Luszczek;Jack Dongarra
Affiliations:
KAUST Supercomputing Laboratory, Thuwal, Saudi Arabia;Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, USA;Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, USA
Venue:
Computer Science - Research and Development
Year:
2012

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Abstract

This paper presents the power profile of two high performance dense linear algebra libraries i.e., LAPACK and PLASMA. The former is based on block algorithms that use the fork-join paradigm to achieve parallel performance. The latter uses fine-grained task parallelism that recasts the computation to operate on submatrices called tiles. In this way tile algorithms are formed. We show results from the power profiling of the most common routines, which permits us to clearly identify the different phases of the computations. This allows us to isolate the bottlenecks in terms of energy efficiency. Our results show that PLASMA surpasses LAPACK not only in terms of performance but also in terms of energy efficiency.