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Performance and productivity of parallel python programming: a study with a CFD test case

Basermann, Achim und Röhrig-Zöllner, Melven und Illmer, Joachim (2015) Performance and productivity of parallel python programming: a study with a CFD test case. In: PyHPC '15 Proceedings of the 5th Workshop on Python for High-Performance and Scientific Computing. ACM New York. PyHPC '15: Proceedings of the 5th Workshop on Python for High-Performance and Scientific Computing; Workshop during SC15: The International Conference for High Performance Computing, Networking, Storage and Analysis, 2015-11-15 - 2015-11-20, Austin, Texas, United States of America. doi: 10.1145/2835857.2835859. ISBN 978 1 4503 4010 6.

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Offizielle URL: http://dl.acm.org/citation.cfm?id=2835859

Kurzfassung

The programming language Python is widely used to create rapidly compact software. However, compared to low-level programming languages like C or Fortran low performance is preventing its use for HPC applications. Efficient parallel programming of multi-core systems and graphic cards is generally a complex task. Python with add-ons might provide a simple approach to program those systems. This paper evaluates the performance of Python implementations with different libraries and compares it to implementations in C or Fortran. As a test case from the field of computational fluid dynamics (CFD) a part of a rotor simulation code was selected. Fortran versions of this code were available for use on single-core, multi-core and graphic-card systems. For all these computer systems, multiple compact versions of the code were implemented in Python with different libraries. For performance analysis of the rotor simulation kernel, a performance model was developed. This model was then employed to assess the performance reached with the different implementations. Performance tests showed that an implementation with Python syntax is six times slower than Fortran on single-core systems. The performance on multi-core systems and graphic cards is about a tenth of the Fortran implementations. A higher performance was achieved by a hybrid implementation in C and Python using Cython. The latter reached about half of the performance of the Fortran implementation.

elib-URL des Eintrags:https://elib.dlr.de/100612/
Dokumentart:Konferenzbeitrag (Vortrag)
Titel:Performance and productivity of parallel python programming: a study with a CFD test case
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Basermann, AchimDLR-KP, SC-VSSNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Röhrig-Zöllner, MelvenDLR-KP, SC-VSSNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Illmer, JoachimDLR-KP, SC-VSSNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:2015
Erschienen in:PyHPC '15 Proceedings of the 5th Workshop on Python for High-Performance and Scientific Computing
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Nein
In ISI Web of Science:Nein
DOI:10.1145/2835857.2835859
Herausgeber:
HerausgeberInstitution und/oder E-Mail-Adresse der HerausgeberHerausgeber-ORCID-iDORCID Put Code
NICHT SPEZIFIZIERTACM Digital LibraryNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Verlag:ACM New York
ISBN:978 1 4503 4010 6
Status:veröffentlicht
Stichwörter:Parallel programming; Python; performance; productivity; helicopter simulation kernel; freewake; performance analysis; performance modelling; multi-core CPU; GPU
Veranstaltungstitel:PyHPC '15: Proceedings of the 5th Workshop on Python for High-Performance and Scientific Computing; Workshop during SC15: The International Conference for High Performance Computing, Networking, Storage and Analysis
Veranstaltungsort:Austin, Texas, United States of America
Veranstaltungsart:internationale Konferenz
Veranstaltungsbeginn:15 November 2015
Veranstaltungsende:20 November 2015
Veranstalter :SIGHPC: ACM Special Interest Group on High Performance Computing; SC15: The International Conference for High Performance Computing, Networking, Storage and Analysis
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Technik für Raumfahrtsysteme
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R SY - Technik für Raumfahrtsysteme
DLR - Teilgebiet (Projekt, Vorhaben):R - Vorhaben SISTEC (alt)
Standort: Köln-Porz
Institute & Einrichtungen:Institut für Simulations- und Softwaretechnik > Verteilte Systeme und Komponentensoftware
Hinterlegt von: Basermann, Dr.-Ing. Achim
Hinterlegt am:09 Dez 2015 16:21
Letzte Änderung:24 Apr 2024 20:06

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