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Performance Engineering and Energy Efficiency of Building Blocks for Large, Sparse Eigenvalue Computations on Heterogeneous Supercomputers

Kreutzer, Moritz and Alvermann, Andreas and Galgon, Martin and Pieper, Andreas and Röhrig-Zöllner, Melven and Shahzad, Faisal and Thies, Jonas and Basermann, Achim and Bishop, Alan R. and Fehske, Holger and Hager, Georg and Lang, Bruno and Wellein, Gerhard (2016) Performance Engineering and Energy Efficiency of Building Blocks for Large, Sparse Eigenvalue Computations on Heterogeneous Supercomputers. In: Software for Exascale Computing - SPPEXA 2013-2015 Lecture Notes on Computer Science and Engineering, 113. Springer. pp. 317-338. ISBN 978-3-319-40528-5.

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Official URL: http://link.springer.com/chapter/10.1007/978-3-319-40528-5_14

Abstract

Numerous challenges have to be mastered as applications in scientific computing are being developed for post-petascale parallel systems. While ample parallelism is usually available in the numerical problems at hand, the efficient use of supercomputer resources requires not only good scalability but also a verifiably effective use of resources on the core, the processor, and the accelerator level. Furthermore, power dissipation and energy consumption are becoming further optimization targets besides time to solution. Performance Engineering (PE) is the pivotal strategy for developing effective parallel code on all levels of modern architectures. In this paper we report on the development and use of low-level parallel building blocks in the GHOST library ("General, Hybrid, and Optimized Sparse Toolkit"). We demonstrate the use of PE in optimizing a density of states computation using the Kernel Polynomial Method, and show that reduction of runtime and reduction of energy are literally the same goal in this case. We also give a brief overview of the capabilities of GHOST and the applications in which it is being used successfully.

Item URL in elib:https://elib.dlr.de/100228/
Document Type:Contribution to a Collection
Title:Performance Engineering and Energy Efficiency of Building Blocks for Large, Sparse Eigenvalue Computations on Heterogeneous Supercomputers
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Kreutzer, MoritzErlangen Regional Computing CenterUNSPECIFIED
Alvermann, AndreasErnst-Moritz-Arndt University of GreifswaldUNSPECIFIED
Galgon, Martingalgon (at) math.uni-wuppertal.deUNSPECIFIED
Pieper, AndreasPieper (at) physik.uni-greifswald.deUNSPECIFIED
Röhrig-Zöllner, MelvenMelven.Roehrig-Zoellner (at) dlr.deUNSPECIFIED
Shahzad, FaisalFaisal.Shahzad (at) rrze.fau.deUNSPECIFIED
Thies, JonasJonas.Thies (at) dlr.deUNSPECIFIED
Basermann, AchimAchim.Basermann (at) dlr.dehttps://orcid.org/0000-0003-3637-3231
Bishop, Alan R.Los Alamos National LaboratoryUNSPECIFIED
Fehske, HolgerErnst-Moritz-Arndt University of GreifswaldUNSPECIFIED
Hager, GeorgErlangen Regional Computing CenterUNSPECIFIED
Lang, Brunolang (at) math.uni-wuppertal.deUNSPECIFIED
Wellein, GerhardErlangen Regional Computing CenterUNSPECIFIED
Date:2016
Journal or Publication Title:Software for Exascale Computing - SPPEXA 2013-2015
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Volume:113
DOI :10.1007/9783319405285_14
Page Range:pp. 317-338
Publisher:Springer
Series Name:Lecture Notes on Computer Science and Engineering
ISBN:978-3-319-40528-5
Status:Published
Keywords:sparse matrix, kernels, heterogeneous supercomputers, eigenvalue computations
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Technik für Raumfahrtsysteme
DLR - Research theme (Project):R - Vorhaben SISTEC
Location: Köln-Porz
Institutes and Institutions:Institut of Simulation and Software Technology > Distributed Systems and Component Software
Institut of Simulation and Software Technology
Deposited By: Thies, Jonas
Deposited On:09 Dec 2015 16:16
Last Modified:31 Jul 2019 19:57

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