Strategies to optimize the LU factorization algorithm on multicore computers
- Autores
- Soler, Janet; Ortiz, Javier; Wolfmann, Aaron Gustavo
- Año de publicación
- 2013
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- Fil: Soler, Janet. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina.
Fil: Ortiz, Javier. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina.
Fil: Wolfmann, Aaron Gustavo. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina.
The number of cores in multicore computers has an irreversible tendency to increase. Also, computers with multiple sockets to insert multicore chips are based on a complex hardware design and are becoming more common. To parallelize the algorithms that run on this type of computers in order to obtain a higher performance rate, is a goal that can only be achieved by taking into account hardware architecture. As hardware evolves, so must software. This leads to old parallelization strategies quickly become obsolete. This paper presents a series of alternatives for parallelization the LU factorization algorithm and its results intended to running on a multicore system. Simple strategies lead to poor results. This study presents complex strategies that merge double levels of parallelism with asynchronous scheduling whose results reach up to the State-of-the-art in the field and even go further.
http://hpc2013.hpclatam.org/talks.html#fullpaper17
Fil: Soler, Janet. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina.
Fil: Ortiz, Javier. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina.
Fil: Wolfmann, Aaron Gustavo. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina.
Ciencias de la Computación - Materia
-
Hardware architecture
Software
Multicore system - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- Repositorio
- Institución
- Universidad Nacional de Córdoba
- OAI Identificador
- oai:rdu.unc.edu.ar:11086/28443
Ver los metadatos del registro completo
id |
RDUUNC_a352aea446259251b0ac8494c1c016b4 |
---|---|
oai_identifier_str |
oai:rdu.unc.edu.ar:11086/28443 |
network_acronym_str |
RDUUNC |
repository_id_str |
2572 |
network_name_str |
Repositorio Digital Universitario (UNC) |
spelling |
Strategies to optimize the LU factorization algorithm on multicore computersSoler, JanetOrtiz, JavierWolfmann, Aaron GustavoHardware architectureSoftwareMulticore systemFil: Soler, Janet. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina.Fil: Ortiz, Javier. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina.Fil: Wolfmann, Aaron Gustavo. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina.The number of cores in multicore computers has an irreversible tendency to increase. Also, computers with multiple sockets to insert multicore chips are based on a complex hardware design and are becoming more common. To parallelize the algorithms that run on this type of computers in order to obtain a higher performance rate, is a goal that can only be achieved by taking into account hardware architecture. As hardware evolves, so must software. This leads to old parallelization strategies quickly become obsolete. This paper presents a series of alternatives for parallelization the LU factorization algorithm and its results intended to running on a multicore system. Simple strategies lead to poor results. This study presents complex strategies that merge double levels of parallelism with asynchronous scheduling whose results reach up to the State-of-the-art in the field and even go further.http://hpc2013.hpclatam.org/talks.html#fullpaper17Fil: Soler, Janet. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina.Fil: Ortiz, Javier. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina.Fil: Wolfmann, Aaron Gustavo. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina.Ciencias de la Computación2013info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://hdl.handle.net/11086/28443enginfo:eu-repo/semantics/openAccessreponame:Repositorio Digital Universitario (UNC)instname:Universidad Nacional de Córdobainstacron:UNC2025-10-16T09:30:11Zoai:rdu.unc.edu.ar:11086/28443Institucionalhttps://rdu.unc.edu.ar/Universidad públicaNo correspondehttp://rdu.unc.edu.ar/oai/snrdoca.unc@gmail.comArgentinaNo correspondeNo correspondeNo correspondeopendoar:25722025-10-16 09:30:12.058Repositorio Digital Universitario (UNC) - Universidad Nacional de Córdobafalse |
dc.title.none.fl_str_mv |
Strategies to optimize the LU factorization algorithm on multicore computers |
title |
Strategies to optimize the LU factorization algorithm on multicore computers |
spellingShingle |
Strategies to optimize the LU factorization algorithm on multicore computers Soler, Janet Hardware architecture Software Multicore system |
title_short |
Strategies to optimize the LU factorization algorithm on multicore computers |
title_full |
Strategies to optimize the LU factorization algorithm on multicore computers |
title_fullStr |
Strategies to optimize the LU factorization algorithm on multicore computers |
title_full_unstemmed |
Strategies to optimize the LU factorization algorithm on multicore computers |
title_sort |
Strategies to optimize the LU factorization algorithm on multicore computers |
dc.creator.none.fl_str_mv |
Soler, Janet Ortiz, Javier Wolfmann, Aaron Gustavo |
author |
Soler, Janet |
author_facet |
Soler, Janet Ortiz, Javier Wolfmann, Aaron Gustavo |
author_role |
author |
author2 |
Ortiz, Javier Wolfmann, Aaron Gustavo |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Hardware architecture Software Multicore system |
topic |
Hardware architecture Software Multicore system |
dc.description.none.fl_txt_mv |
Fil: Soler, Janet. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina. Fil: Ortiz, Javier. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina. Fil: Wolfmann, Aaron Gustavo. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina. The number of cores in multicore computers has an irreversible tendency to increase. Also, computers with multiple sockets to insert multicore chips are based on a complex hardware design and are becoming more common. To parallelize the algorithms that run on this type of computers in order to obtain a higher performance rate, is a goal that can only be achieved by taking into account hardware architecture. As hardware evolves, so must software. This leads to old parallelization strategies quickly become obsolete. This paper presents a series of alternatives for parallelization the LU factorization algorithm and its results intended to running on a multicore system. Simple strategies lead to poor results. This study presents complex strategies that merge double levels of parallelism with asynchronous scheduling whose results reach up to the State-of-the-art in the field and even go further. http://hpc2013.hpclatam.org/talks.html#fullpaper17 Fil: Soler, Janet. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina. Fil: Ortiz, Javier. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina. Fil: Wolfmann, Aaron Gustavo. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina. Ciencias de la Computación |
description |
Fil: Soler, Janet. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Laboratorio de Computación; Argentina. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion 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://hdl.handle.net/11086/28443 |
url |
http://hdl.handle.net/11086/28443 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositorio Digital Universitario (UNC) instname:Universidad Nacional de Córdoba instacron:UNC |
reponame_str |
Repositorio Digital Universitario (UNC) |
collection |
Repositorio Digital Universitario (UNC) |
instname_str |
Universidad Nacional de Córdoba |
instacron_str |
UNC |
institution |
UNC |
repository.name.fl_str_mv |
Repositorio Digital Universitario (UNC) - Universidad Nacional de Córdoba |
repository.mail.fl_str_mv |
oca.unc@gmail.com |
_version_ |
1846143377264869376 |
score |
12.712165 |