Executing linear algebra kernels in heterogeneous distributed infrastructures with PyCOMPSs

Python is a popular programming language due to the simplicity of its syntax, while still achieving a good performance even being an interpreted language. The adoption from multiple scientific communities has evolved in the emergence of a large number of libraries and modules, which has helped to pu...

Descripción completa

Detalles Bibliográficos
Autores: Amela Milian, Ramon, Ramon-cortés Vilarrodona, Cristian, Ejarque, Jorge|||0000-0003-4725-5097, Conejero, Javier, Badia Sala, Rosa Maria|||0000-0003-2941-5499
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/125116
Acceso en línea:https://hdl.handle.net/2117/125116
https://dx.doi.org/10.2516/ogst/2018047
Access Level:acceso abierto
Palabra clave:Parallel programming (Computer science)
Python
Programming language
Task-based programming
Programació (Ordinadors)
Àrees temàtiques de la UPC::Informàtica
id ES_cafca2ca7a7f6b76c0b92ccc33d39388
oai_identifier_str oai:upcommons.upc.edu:2117/125116
network_acronym_str ES
network_name_str España
repository_id_str
spelling Executing linear algebra kernels in heterogeneous distributed infrastructures with PyCOMPSsAmela Milian, RamonRamon-cortés Vilarrodona, CristianEjarque, Jorge|||0000-0003-4725-5097Conejero, JavierBadia Sala, Rosa Maria|||0000-0003-2941-5499Parallel programming (Computer science)PythonProgramming languageTask-based programmingProgramació (Ordinadors)Àrees temàtiques de la UPC::InformàticaPython is a popular programming language due to the simplicity of its syntax, while still achieving a good performance even being an interpreted language. The adoption from multiple scientific communities has evolved in the emergence of a large number of libraries and modules, which has helped to put Python on the top of the list of the programming languages [1]. Task-based programming has been proposed in the recent years as an alternative parallel programming model. PyCOMPSs follows such approach for Python, and this paper presents its extensions to combine task-based parallelism and thread-level parallelism. Also, we present how PyCOMPSs has been adapted to support heterogeneous architectures, including Xeon Phi and GPUs. Results obtained with linear algebra benchmarks demonstrate that significant performance can be obtained with a few lines of Python.This work has been supported by the Spanish Government (SEV2015-0493), by the Spanish Ministry of Science and Innovation (contract TIN2015-65316-P), by Generalitat de Catalunya (contracts 2014-SGR-1051 and 2014-SGR-1272). Javier Conejero postdoctoral contract is co-financed by the Ministry of Economy and Competitiveness under Juan de la Cierva Formación postdoctoral fellowship number FJCI-2015-24651. Cristian Ramon-Cortes predoctoral contract is financed by the Ministry of Economy and Competitiveness under the contract BES-2016-076791. This work is supported by the Intel-BSC Exascale Lab. This work has been supported by the European Commission through the Horizon 2020 Research and Innovation program under contract 687584 (TANGO project).Peer ReviewedEDP Open20182018-10-2420182018-11-27journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/125116https://dx.doi.org/10.2516/ogst/2018047reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengMinisterio de Economía y Competitividad http://doi.org/10.13039/501100003329 TIN2015-65316-P COMPUTACION DE ALTAS PRESTACIONES VIIMinisterio de Economía y Competitividad http://doi.org/10.13039/501100003329 FJCI-2015-24651 FJCI-2015-24651European Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 687584 Transparent heterogeneous hardware Architecture deployment for eNergy Gain in Operationopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivs 4.0 Spainhttp://creativecommons.org/licenses/by-nc-nd/4.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/1251162026-05-27T15:37:01Z
dc.title.none.fl_str_mv Executing linear algebra kernels in heterogeneous distributed infrastructures with PyCOMPSs
title Executing linear algebra kernels in heterogeneous distributed infrastructures with PyCOMPSs
spellingShingle Executing linear algebra kernels in heterogeneous distributed infrastructures with PyCOMPSs
Amela Milian, Ramon
Parallel programming (Computer science)
Python
Programming language
Task-based programming
Programació (Ordinadors)
Àrees temàtiques de la UPC::Informàtica
title_short Executing linear algebra kernels in heterogeneous distributed infrastructures with PyCOMPSs
title_full Executing linear algebra kernels in heterogeneous distributed infrastructures with PyCOMPSs
title_fullStr Executing linear algebra kernels in heterogeneous distributed infrastructures with PyCOMPSs
title_full_unstemmed Executing linear algebra kernels in heterogeneous distributed infrastructures with PyCOMPSs
title_sort Executing linear algebra kernels in heterogeneous distributed infrastructures with PyCOMPSs
dc.creator.none.fl_str_mv Amela Milian, Ramon
Ramon-cortés Vilarrodona, Cristian
Ejarque, Jorge|||0000-0003-4725-5097
Conejero, Javier
Badia Sala, Rosa Maria|||0000-0003-2941-5499
author Amela Milian, Ramon
author_facet Amela Milian, Ramon
Ramon-cortés Vilarrodona, Cristian
Ejarque, Jorge|||0000-0003-4725-5097
Conejero, Javier
Badia Sala, Rosa Maria|||0000-0003-2941-5499
author_role author
author2 Ramon-cortés Vilarrodona, Cristian
Ejarque, Jorge|||0000-0003-4725-5097
Conejero, Javier
Badia Sala, Rosa Maria|||0000-0003-2941-5499
author2_role author
author
author
author
dc.subject.none.fl_str_mv Parallel programming (Computer science)
Python
Programming language
Task-based programming
Programació (Ordinadors)
Àrees temàtiques de la UPC::Informàtica
topic Parallel programming (Computer science)
Python
Programming language
Task-based programming
Programació (Ordinadors)
Àrees temàtiques de la UPC::Informàtica
description Python is a popular programming language due to the simplicity of its syntax, while still achieving a good performance even being an interpreted language. The adoption from multiple scientific communities has evolved in the emergence of a large number of libraries and modules, which has helped to put Python on the top of the list of the programming languages [1]. Task-based programming has been proposed in the recent years as an alternative parallel programming model. PyCOMPSs follows such approach for Python, and this paper presents its extensions to combine task-based parallelism and thread-level parallelism. Also, we present how PyCOMPSs has been adapted to support heterogeneous architectures, including Xeon Phi and GPUs. Results obtained with linear algebra benchmarks demonstrate that significant performance can be obtained with a few lines of Python.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-10-24
2018
2018-11-27
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/125116
https://dx.doi.org/10.2516/ogst/2018047
url https://hdl.handle.net/2117/125116
https://dx.doi.org/10.2516/ogst/2018047
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Ministerio de Economía y Competitividad http://doi.org/10.13039/501100003329 TIN2015-65316-P COMPUTACION DE ALTAS PRESTACIONES VII
Ministerio de Economía y Competitividad http://doi.org/10.13039/501100003329 FJCI-2015-24651 FJCI-2015-24651
European Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 687584 Transparent heterogeneous hardware Architecture deployment for eNergy Gain in Operation
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 4.0 Spain
http://creativecommons.org/licenses/by-nc-nd/4.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 4.0 Spain
http://creativecommons.org/licenses/by-nc-nd/4.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv EDP Open
publisher.none.fl_str_mv EDP Open
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869419527143424000
score 15.300719

Similares en LA Referencia