Mapping realistic data sets on parallel computers

Mapping data to parallel computers aims at minimizing the execution time of the associated application. However, it can take an unacceptable amount of time in comparison with the execution time of the application if the size of the problem is large. The authors propose reducing the problem size by a...

Full description

Saved in:
Bibliographic Details
Main Author: Mansour, N. (author)
Other Authors: Ponnusamy, R. (author), Choudhary, A. (author), Fox, G.C. (author)
Format: conferenceObject
Published: 1993
Online Access:http://hdl.handle.net/10725/7936
http://dx.doi.org/10.1109/IPPS.1993.262867
http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php
https://ieeexplore.ieee.org/abstract/document/262867/
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1864513483488362496
author Mansour, N.
author2 Ponnusamy, R.
Choudhary, A.
Fox, G.C.
author2_role author
author
author
author_facet Mansour, N.
Ponnusamy, R.
Choudhary, A.
Fox, G.C.
author_role author
dc.creator.none.fl_str_mv Mansour, N.
Ponnusamy, R.
Choudhary, A.
Fox, G.C.
dc.date.none.fl_str_mv 1993
2018-05-24T12:44:18Z
2018-05-24T12:44:18Z
2018-05-24
dc.identifier.none.fl_str_mv 0-8186-3442-1
http://hdl.handle.net/10725/7936
http://dx.doi.org/10.1109/IPPS.1993.262867
Ponnusamy, R., Mansour, N., Choudhary, A., & Fox, G. C. (1993, April). Mapping realistic data sets on parallel computers. In Parallel Processing Symposium, 1993., Proceedings of Seventh International (pp. 123-128). IEEE.
http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php
https://ieeexplore.ieee.org/abstract/document/262867/
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv IEEE Xplore
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.title.none.fl_str_mv Mapping realistic data sets on parallel computers
dc.type.none.fl_str_mv Conference Paper / Proceeding
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/conferenceObject
description Mapping data to parallel computers aims at minimizing the execution time of the associated application. However, it can take an unacceptable amount of time in comparison with the execution time of the application if the size of the problem is large. The authors propose reducing the problem size by a mapping-oriented graph contraction technique. They present a graph contraction (GC) heuristic algorithm that yields a smaller representation of the problem, to which mapping is then applied. The experimental results show that the GC algorithm still leads to good quality mapping solutions to the original problem, while producing remarkable reductions in mapping time. The GC algorithm allows large-scale mapping to become efficient, especially when slow but high-quality mappers are used.
eu_rights_str_mv openAccess
format conferenceObject
id LAURepo_e17ebd72c953c525d83f83eb460bcc10
identifier_str_mv 0-8186-3442-1
Ponnusamy, R., Mansour, N., Choudhary, A., & Fox, G. C. (1993, April). Mapping realistic data sets on parallel computers. In Parallel Processing Symposium, 1993., Proceedings of Seventh International (pp. 123-128). IEEE.
language_invalid_str_mv en
network_acronym_str LAURepo
network_name_str Lebanese American University repository
oai_identifier_str oai:laur.lau.edu.lb:10725/7936
publishDate 1993
publisher.none.fl_str_mv IEEE Xplore
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling Mapping realistic data sets on parallel computersMansour, N.Ponnusamy, R.Choudhary, A.Fox, G.C.Mapping data to parallel computers aims at minimizing the execution time of the associated application. However, it can take an unacceptable amount of time in comparison with the execution time of the application if the size of the problem is large. The authors propose reducing the problem size by a mapping-oriented graph contraction technique. They present a graph contraction (GC) heuristic algorithm that yields a smaller representation of the problem, to which mapping is then applied. The experimental results show that the GC algorithm still leads to good quality mapping solutions to the original problem, while producing remarkable reductions in mapping time. The GC algorithm allows large-scale mapping to become efficient, especially when slow but high-quality mappers are used.N/AIEEE Xplore2018-05-24T12:44:18Z2018-05-24T12:44:18Z19932018-05-24Conference Paper / Proceedinginfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject0-8186-3442-1http://hdl.handle.net/10725/7936http://dx.doi.org/10.1109/IPPS.1993.262867Ponnusamy, R., Mansour, N., Choudhary, A., & Fox, G. C. (1993, April). Mapping realistic data sets on parallel computers. In Parallel Processing Symposium, 1993., Proceedings of Seventh International (pp. 123-128). IEEE.http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.phphttps://ieeexplore.ieee.org/abstract/document/262867/eninfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/79362021-03-19T10:43:07Z
spellingShingle Mapping realistic data sets on parallel computers
Mansour, N.
status_str publishedVersion
title Mapping realistic data sets on parallel computers
title_full Mapping realistic data sets on parallel computers
title_fullStr Mapping realistic data sets on parallel computers
title_full_unstemmed Mapping realistic data sets on parallel computers
title_short Mapping realistic data sets on parallel computers
title_sort Mapping realistic data sets on parallel computers
url http://hdl.handle.net/10725/7936
http://dx.doi.org/10.1109/IPPS.1993.262867
http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php
https://ieeexplore.ieee.org/abstract/document/262867/