Efficiency analysis of a physical problem: different parallel computational approaches for a dynamical integrator evolution

Autores
Gaudiani, Adriana; Carusela, Florencia; Soba, Alejandro
Año de publicación
2013
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
A great challenge for scientists is to execute their computational applications efficiently. Nowadays, parallel programming has become a fundamental key to achieve this goal. High-performance computing provides a solution to exploit parallel architectures in order to get optimal performance. Both parallel programming model and the system architecture will maximize the benefits if both together are suitable to the inherent parallelism of the problem. We compared three parallelized versions of our algorithm when applied to the study of the heat transport phenomenon in a low dimensional system. We qualitatively analyze the obtained performance data based on the own characteristics of multicore architecture, shared memory and NVIDIA graphical multiprocesors related to the traditional programing models provided by MPI and OpenMP, and Cuda programming environment. We conclude that GPUs parallel computing architecture is the most suitable programing model to achieve a better performance of our algorithm. We obtained an improvement of 15X, quite good for a program whose efficiency is strongly degraded by an integration process that essentially must be carried out in a serial way due to the dependence of the data.
WPDP- XIII Workshop procesamiento distribuido y paralelo
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Parallel Architectures
Parallel programming
System architectures
Shared memory
computational applications efficiently
performance computing
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/31742

id SEDICI_b502f6e0f7ef700112af31d9015b424a
oai_identifier_str oai:sedici.unlp.edu.ar:10915/31742
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Efficiency analysis of a physical problem: different parallel computational approaches for a dynamical integrator evolutionGaudiani, AdrianaCarusela, FlorenciaSoba, AlejandroCiencias InformáticasParallel ArchitecturesParallel programmingSystem architecturesShared memorycomputational applications efficientlyperformance computingA great challenge for scientists is to execute their computational applications efficiently. Nowadays, parallel programming has become a fundamental key to achieve this goal. High-performance computing provides a solution to exploit parallel architectures in order to get optimal performance. Both parallel programming model and the system architecture will maximize the benefits if both together are suitable to the inherent parallelism of the problem. We compared three parallelized versions of our algorithm when applied to the study of the heat transport phenomenon in a low dimensional system. We qualitatively analyze the obtained performance data based on the own characteristics of multicore architecture, shared memory and NVIDIA graphical multiprocesors related to the traditional programing models provided by MPI and OpenMP, and Cuda programming environment. We conclude that GPUs parallel computing architecture is the most suitable programing model to achieve a better performance of our algorithm. We obtained an improvement of 15X, quite good for a program whose efficiency is strongly degraded by an integration process that essentially must be carried out in a serial way due to the dependence of the data.WPDP- XIII Workshop procesamiento distribuido y paraleloRed de Universidades con Carreras en Informática (RedUNCI)2013-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/31742enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:58:05Zoai:sedici.unlp.edu.ar:10915/31742Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:58:05.907SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Efficiency analysis of a physical problem: different parallel computational approaches for a dynamical integrator evolution
title Efficiency analysis of a physical problem: different parallel computational approaches for a dynamical integrator evolution
spellingShingle Efficiency analysis of a physical problem: different parallel computational approaches for a dynamical integrator evolution
Gaudiani, Adriana
Ciencias Informáticas
Parallel Architectures
Parallel programming
System architectures
Shared memory
computational applications efficiently
performance computing
title_short Efficiency analysis of a physical problem: different parallel computational approaches for a dynamical integrator evolution
title_full Efficiency analysis of a physical problem: different parallel computational approaches for a dynamical integrator evolution
title_fullStr Efficiency analysis of a physical problem: different parallel computational approaches for a dynamical integrator evolution
title_full_unstemmed Efficiency analysis of a physical problem: different parallel computational approaches for a dynamical integrator evolution
title_sort Efficiency analysis of a physical problem: different parallel computational approaches for a dynamical integrator evolution
dc.creator.none.fl_str_mv Gaudiani, Adriana
Carusela, Florencia
Soba, Alejandro
author Gaudiani, Adriana
author_facet Gaudiani, Adriana
Carusela, Florencia
Soba, Alejandro
author_role author
author2 Carusela, Florencia
Soba, Alejandro
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Parallel Architectures
Parallel programming
System architectures
Shared memory
computational applications efficiently
performance computing
topic Ciencias Informáticas
Parallel Architectures
Parallel programming
System architectures
Shared memory
computational applications efficiently
performance computing
dc.description.none.fl_txt_mv A great challenge for scientists is to execute their computational applications efficiently. Nowadays, parallel programming has become a fundamental key to achieve this goal. High-performance computing provides a solution to exploit parallel architectures in order to get optimal performance. Both parallel programming model and the system architecture will maximize the benefits if both together are suitable to the inherent parallelism of the problem. We compared three parallelized versions of our algorithm when applied to the study of the heat transport phenomenon in a low dimensional system. We qualitatively analyze the obtained performance data based on the own characteristics of multicore architecture, shared memory and NVIDIA graphical multiprocesors related to the traditional programing models provided by MPI and OpenMP, and Cuda programming environment. We conclude that GPUs parallel computing architecture is the most suitable programing model to achieve a better performance of our algorithm. We obtained an improvement of 15X, quite good for a program whose efficiency is strongly degraded by an integration process that essentially must be carried out in a serial way due to the dependence of the data.
WPDP- XIII Workshop procesamiento distribuido y paralelo
Red de Universidades con Carreras en Informática (RedUNCI)
description A great challenge for scientists is to execute their computational applications efficiently. Nowadays, parallel programming has become a fundamental key to achieve this goal. High-performance computing provides a solution to exploit parallel architectures in order to get optimal performance. Both parallel programming model and the system architecture will maximize the benefits if both together are suitable to the inherent parallelism of the problem. We compared three parallelized versions of our algorithm when applied to the study of the heat transport phenomenon in a low dimensional system. We qualitatively analyze the obtained performance data based on the own characteristics of multicore architecture, shared memory and NVIDIA graphical multiprocesors related to the traditional programing models provided by MPI and OpenMP, and Cuda programming environment. We conclude that GPUs parallel computing architecture is the most suitable programing model to achieve a better performance of our algorithm. We obtained an improvement of 15X, quite good for a program whose efficiency is strongly degraded by an integration process that essentially must be carried out in a serial way due to the dependence of the data.
publishDate 2013
dc.date.none.fl_str_mv 2013-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/31742
url http://sedici.unlp.edu.ar/handle/10915/31742
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
_version_ 1844615843221078016
score 13.070432