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

Handle URI:
http://hdl.handle.net/10754/575552
Title:
Profiling high performance dense linear algebra algorithms on multicore architectures for power and energy efficiency
Authors:
Ltaief, Hatem ( 0000-0002-6897-1095 ) ; Luszczek, Piotr R.; Dongarra, Jack
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. © 2011 Springer-Verlag.
KAUST Department:
KAUST Supercomputing Laboratory (KSL); Extreme Computing Research Center
Publisher:
Springer Nature
Journal:
Computer Science - Research and Development
Issue Date:
31-Aug-2011
DOI:
10.1007/s00450-011-0191-z
Type:
Article
ISSN:
18652034
Appears in Collections:
Articles; KAUST Supercomputing Laboratory (KSL); Extreme Computing Research Center

Full metadata record

DC FieldValue Language
dc.contributor.authorLtaief, Hatemen
dc.contributor.authorLuszczek, Piotr R.en
dc.contributor.authorDongarra, Jacken
dc.date.accessioned2015-08-24T08:32:40Zen
dc.date.available2015-08-24T08:32:40Zen
dc.date.issued2011-08-31en
dc.identifier.issn18652034en
dc.identifier.doi10.1007/s00450-011-0191-zen
dc.identifier.urihttp://hdl.handle.net/10754/575552en
dc.description.abstractThis 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. © 2011 Springer-Verlag.en
dc.publisherSpringer Natureen
dc.subjectDense linear algebraen
dc.subjectEnergy efficiencyen
dc.subjectMulticore architecturesen
dc.subjectPower profileen
dc.subjectTile algorithmsen
dc.titleProfiling high performance dense linear algebra algorithms on multicore architectures for power and energy efficiencyen
dc.typeArticleen
dc.contributor.departmentKAUST Supercomputing Laboratory (KSL)en
dc.contributor.departmentExtreme Computing Research Centeren
dc.identifier.journalComputer Science - Research and Developmenten
dc.contributor.institutionDepartment of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, United Statesen
kaust.authorLtaief, Hatemen
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