Multilevel Parallelization: Grid Methods for Solving Direct and Inverse Problems

Sofya Titarenko, Igor Kulikov, Igor Chernykh, Maxim A. Shishlenin, Olga Krivorot'ko, Dmitry A. Voronov, Mark Hildyard

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

Abstract

In this paper we present grid methods which we have developed for solving direct and inverse problems, and their realization with different levels of optimization. We have focused on solving systems of hyperbolic equations using finite difference and finite volume numerical methods on multicore architectures. Several levels of parallelism have been applied: geometric decomposition of the calculative domain, workload distribution over threads within OpenMP directives, and vectorization. The run-time efficiency of these methods has been investigated. These developments have been tested using the astrophysics code AstroPhi on a hybrid cluster Polytechnic RSC PetaStream (consisting of Intel Xeon Phi accelerators) and a geophysics (seismic wave) code on an Intel Core i7-3930K multicore processor. We present the results of the calculations and study MPI run-time energy efficiency.
LanguageEnglish
Title of host publicationSupercomputing
Subtitle of host publicationSecond Russian Supercomputing Days, RuSCDays 2016, Moscow, Russia, September 26–27, 2016, Revised Selected Papers
EditorsVladimir Voevodin, Sergey Sobolev
Place of PublicationCham
PublisherSpringer International Publishing AG
Pages118-131
Number of pages14
Edition1st
ISBN (Electronic)9783319556697
ISBN (Print)9783319556680
DOIs
Publication statusPublished - 12 Mar 2017
Externally publishedYes
EventSecond Russian Supercomputing Days 2016 - Moscow, Russian Federation
Duration: 26 Sep 201627 Sep 2016

Publication series

NameCommunications in Computer and Information Science
PublisherSpringer International Publishing AG
ISSN (Print)1865-0929

Conference

ConferenceSecond Russian Supercomputing Days 2016
Abbreviated titleRuSCDays 2016
CountryRussian Federation
CityMoscow
Period26/09/1627/09/16

Fingerprint

Astrophysics
Geophysics
Seismic waves
Inverse problems
Particle accelerators
Energy efficiency
Numerical methods
Decomposition

Cite this

Titarenko, S., Kulikov, I., Chernykh, I., Shishlenin, M. A., Krivorot'ko, O., Voronov, D. A., & Hildyard, M. (2017). Multilevel Parallelization: Grid Methods for Solving Direct and Inverse Problems. In V. Voevodin, & S. Sobolev (Eds.), Supercomputing: Second Russian Supercomputing Days, RuSCDays 2016, Moscow, Russia, September 26–27, 2016, Revised Selected Papers (1st ed., pp. 118-131). (Communications in Computer and Information Science). Cham: Springer International Publishing AG. https://doi.org/10.1007/978-3-319-55669-7_10
Titarenko, Sofya ; Kulikov, Igor ; Chernykh, Igor ; Shishlenin, Maxim A. ; Krivorot'ko, Olga ; Voronov, Dmitry A. ; Hildyard, Mark. / Multilevel Parallelization : Grid Methods for Solving Direct and Inverse Problems. Supercomputing: Second Russian Supercomputing Days, RuSCDays 2016, Moscow, Russia, September 26–27, 2016, Revised Selected Papers . editor / Vladimir Voevodin ; Sergey Sobolev. 1st. ed. Cham : Springer International Publishing AG, 2017. pp. 118-131 (Communications in Computer and Information Science).
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abstract = "In this paper we present grid methods which we have developed for solving direct and inverse problems, and their realization with different levels of optimization. We have focused on solving systems of hyperbolic equations using finite difference and finite volume numerical methods on multicore architectures. Several levels of parallelism have been applied: geometric decomposition of the calculative domain, workload distribution over threads within OpenMP directives, and vectorization. The run-time efficiency of these methods has been investigated. These developments have been tested using the astrophysics code AstroPhi on a hybrid cluster Polytechnic RSC PetaStream (consisting of Intel Xeon Phi accelerators) and a geophysics (seismic wave) code on an Intel Core i7-3930K multicore processor. We present the results of the calculations and study MPI run-time energy efficiency.",
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Titarenko, S, Kulikov, I, Chernykh, I, Shishlenin, MA, Krivorot'ko, O, Voronov, DA & Hildyard, M 2017, Multilevel Parallelization: Grid Methods for Solving Direct and Inverse Problems. in V Voevodin & S Sobolev (eds), Supercomputing: Second Russian Supercomputing Days, RuSCDays 2016, Moscow, Russia, September 26–27, 2016, Revised Selected Papers . 1st edn, Communications in Computer and Information Science, Springer International Publishing AG, Cham, pp. 118-131, Second Russian Supercomputing Days 2016, Moscow, Russian Federation, 26/09/16. https://doi.org/10.1007/978-3-319-55669-7_10

Multilevel Parallelization : Grid Methods for Solving Direct and Inverse Problems. / Titarenko, Sofya; Kulikov, Igor; Chernykh, Igor; Shishlenin, Maxim A.; Krivorot'ko, Olga; Voronov, Dmitry A.; Hildyard, Mark.

Supercomputing: Second Russian Supercomputing Days, RuSCDays 2016, Moscow, Russia, September 26–27, 2016, Revised Selected Papers . ed. / Vladimir Voevodin; Sergey Sobolev. 1st. ed. Cham : Springer International Publishing AG, 2017. p. 118-131 (Communications in Computer and Information Science).

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

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AU - Titarenko, Sofya

AU - Kulikov, Igor

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AU - Shishlenin, Maxim A.

AU - Krivorot'ko, Olga

AU - Voronov, Dmitry A.

AU - Hildyard, Mark

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AB - In this paper we present grid methods which we have developed for solving direct and inverse problems, and their realization with different levels of optimization. We have focused on solving systems of hyperbolic equations using finite difference and finite volume numerical methods on multicore architectures. Several levels of parallelism have been applied: geometric decomposition of the calculative domain, workload distribution over threads within OpenMP directives, and vectorization. The run-time efficiency of these methods has been investigated. These developments have been tested using the astrophysics code AstroPhi on a hybrid cluster Polytechnic RSC PetaStream (consisting of Intel Xeon Phi accelerators) and a geophysics (seismic wave) code on an Intel Core i7-3930K multicore processor. We present the results of the calculations and study MPI run-time energy efficiency.

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A2 - Sobolev, Sergey

PB - Springer International Publishing AG

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Titarenko S, Kulikov I, Chernykh I, Shishlenin MA, Krivorot'ko O, Voronov DA et al. Multilevel Parallelization: Grid Methods for Solving Direct and Inverse Problems. In Voevodin V, Sobolev S, editors, Supercomputing: Second Russian Supercomputing Days, RuSCDays 2016, Moscow, Russia, September 26–27, 2016, Revised Selected Papers . 1st ed. Cham: Springer International Publishing AG. 2017. p. 118-131. (Communications in Computer and Information Science). https://doi.org/10.1007/978-3-319-55669-7_10