Linear Programming-Based Affinity Scheduling of Independent Tasks on Heterogeneous Computing Systems

Resource management systems (RMS) are an important component in heterogeneous computing (HC) systems. One of the jobs of an RMS is the mapping of arriving tasks onto the machines of the HC system. Many different mapping heuristics have been proposed in recent years. However, most of these heuristics...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on parallel and distributed systems 2008-12, Vol.19 (12), p.1671-1682
Hauptverfasser: Al-Azzoni, I., Down, D.G.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 1682
container_issue 12
container_start_page 1671
container_title IEEE transactions on parallel and distributed systems
container_volume 19
creator Al-Azzoni, I.
Down, D.G.
description Resource management systems (RMS) are an important component in heterogeneous computing (HC) systems. One of the jobs of an RMS is the mapping of arriving tasks onto the machines of the HC system. Many different mapping heuristics have been proposed in recent years. However, most of these heuristics suffer from several limitations. One of these limitations is the performance degradation that results from using outdated global information about the status of all machines in the HC system. This paper proposes several heuristics which address this limitation by only requiring partial information in making the mapping decisions. These heuristics utilize the solution to a linear programming (LP) problem which maximizes the system capacity. Simulation results show that our heuristics perform very competitively while requiring dramatically less information.
doi_str_mv 10.1109/TPDS.2008.59
format Article
fullrecord <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_proquest_miscellaneous_875054740</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>4492769</ieee_id><sourcerecordid>34441305</sourcerecordid><originalsourceid>FETCH-LOGICAL-c377t-13be58aedb39150d8353accd3362038f82e77ae088fb79e3617aee55251de9fd3</originalsourceid><addsrcrecordid>eNqF0TtPwzAUBeAIgQQUNjYWiwEWUq5fiT1CeUqVQGqZLTe-gUCTFDsZ-u9xKGJggMUP-dPRtU6SHFEYUwr6Yv50PRszADWWeivZo1KqlFHFt-MZhEw1o3o32Q_hDYAKCWIvcdOqQevJk29fvK3rqnlJr2xARy7Lsmqqbk1mxSu6fhlfSFuSh8bhCuPSdGRuw3sgbUPuscMYgA22fSCTtl713eBn69BhHQ6SndIuAx5-76Pk-fZmPrlPp493D5PLaVrwPO9SyhcolUW34JpKcIpLbovCcZ4x4KpUDPPcIihVLnKNPKPxhlIySR3q0vFRcrbJXfn2o8fQmboKBS6X9mswoyEmZQqyf6XKJUiRC4jy9E_JhRCUg4zw5Bd8a3vfxP8aTRlTnAod0fkGFb4NwWNpVr6qrV8bCmbo0AwdmqFDIwd-vOEVIv5QITTLM80_ARchl7c</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>912283149</pqid></control><display><type>article</type><title>Linear Programming-Based Affinity Scheduling of Independent Tasks on Heterogeneous Computing Systems</title><source>IEEE Electronic Library (IEL)</source><creator>Al-Azzoni, I. ; Down, D.G.</creator><creatorcontrib>Al-Azzoni, I. ; Down, D.G.</creatorcontrib><description>Resource management systems (RMS) are an important component in heterogeneous computing (HC) systems. One of the jobs of an RMS is the mapping of arriving tasks onto the machines of the HC system. Many different mapping heuristics have been proposed in recent years. However, most of these heuristics suffer from several limitations. One of these limitations is the performance degradation that results from using outdated global information about the status of all machines in the HC system. This paper proposes several heuristics which address this limitation by only requiring partial information in making the mapping decisions. These heuristics utilize the solution to a linear programming (LP) problem which maximizes the system capacity. Simulation results show that our heuristics perform very competitively while requiring dramatically less information.</description><identifier>ISSN: 1045-9219</identifier><identifier>EISSN: 1558-2183</identifier><identifier>DOI: 10.1109/TPDS.2008.59</identifier><identifier>CODEN: ITDSEO</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Affinity ; Availability ; Computation ; Computational modeling ; Computer applications ; Computer networks ; Computer simulation ; Degradation ; distributed systems ; heterogeneous processors ; Heuristic ; Linear programming ; load balancing ; Load management ; Mapping ; Processor scheduling ; Queueing analysis ; queueing theory ; Resource management ; Resources management ; Scheduling ; Tasks</subject><ispartof>IEEE transactions on parallel and distributed systems, 2008-12, Vol.19 (12), p.1671-1682</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2008</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c377t-13be58aedb39150d8353accd3362038f82e77ae088fb79e3617aee55251de9fd3</citedby><cites>FETCH-LOGICAL-c377t-13be58aedb39150d8353accd3362038f82e77ae088fb79e3617aee55251de9fd3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4492769$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,777,781,793,27905,27906,54739</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4492769$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Al-Azzoni, I.</creatorcontrib><creatorcontrib>Down, D.G.</creatorcontrib><title>Linear Programming-Based Affinity Scheduling of Independent Tasks on Heterogeneous Computing Systems</title><title>IEEE transactions on parallel and distributed systems</title><addtitle>TPDS</addtitle><description>Resource management systems (RMS) are an important component in heterogeneous computing (HC) systems. One of the jobs of an RMS is the mapping of arriving tasks onto the machines of the HC system. Many different mapping heuristics have been proposed in recent years. However, most of these heuristics suffer from several limitations. One of these limitations is the performance degradation that results from using outdated global information about the status of all machines in the HC system. This paper proposes several heuristics which address this limitation by only requiring partial information in making the mapping decisions. These heuristics utilize the solution to a linear programming (LP) problem which maximizes the system capacity. Simulation results show that our heuristics perform very competitively while requiring dramatically less information.</description><subject>Affinity</subject><subject>Availability</subject><subject>Computation</subject><subject>Computational modeling</subject><subject>Computer applications</subject><subject>Computer networks</subject><subject>Computer simulation</subject><subject>Degradation</subject><subject>distributed systems</subject><subject>heterogeneous processors</subject><subject>Heuristic</subject><subject>Linear programming</subject><subject>load balancing</subject><subject>Load management</subject><subject>Mapping</subject><subject>Processor scheduling</subject><subject>Queueing analysis</subject><subject>queueing theory</subject><subject>Resource management</subject><subject>Resources management</subject><subject>Scheduling</subject><subject>Tasks</subject><issn>1045-9219</issn><issn>1558-2183</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNqF0TtPwzAUBeAIgQQUNjYWiwEWUq5fiT1CeUqVQGqZLTe-gUCTFDsZ-u9xKGJggMUP-dPRtU6SHFEYUwr6Yv50PRszADWWeivZo1KqlFHFt-MZhEw1o3o32Q_hDYAKCWIvcdOqQevJk29fvK3rqnlJr2xARy7Lsmqqbk1mxSu6fhlfSFuSh8bhCuPSdGRuw3sgbUPuscMYgA22fSCTtl713eBn69BhHQ6SndIuAx5-76Pk-fZmPrlPp493D5PLaVrwPO9SyhcolUW34JpKcIpLbovCcZ4x4KpUDPPcIihVLnKNPKPxhlIySR3q0vFRcrbJXfn2o8fQmboKBS6X9mswoyEmZQqyf6XKJUiRC4jy9E_JhRCUg4zw5Bd8a3vfxP8aTRlTnAod0fkGFb4NwWNpVr6qrV8bCmbo0AwdmqFDIwd-vOEVIv5QITTLM80_ARchl7c</recordid><startdate>20081201</startdate><enddate>20081201</enddate><creator>Al-Azzoni, I.</creator><creator>Down, D.G.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>F28</scope><scope>FR3</scope></search><sort><creationdate>20081201</creationdate><title>Linear Programming-Based Affinity Scheduling of Independent Tasks on Heterogeneous Computing Systems</title><author>Al-Azzoni, I. ; Down, D.G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c377t-13be58aedb39150d8353accd3362038f82e77ae088fb79e3617aee55251de9fd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Affinity</topic><topic>Availability</topic><topic>Computation</topic><topic>Computational modeling</topic><topic>Computer applications</topic><topic>Computer networks</topic><topic>Computer simulation</topic><topic>Degradation</topic><topic>distributed systems</topic><topic>heterogeneous processors</topic><topic>Heuristic</topic><topic>Linear programming</topic><topic>load balancing</topic><topic>Load management</topic><topic>Mapping</topic><topic>Processor scheduling</topic><topic>Queueing analysis</topic><topic>queueing theory</topic><topic>Resource management</topic><topic>Resources management</topic><topic>Scheduling</topic><topic>Tasks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Al-Azzoni, I.</creatorcontrib><creatorcontrib>Down, D.G.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE transactions on parallel and distributed systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Al-Azzoni, I.</au><au>Down, D.G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Linear Programming-Based Affinity Scheduling of Independent Tasks on Heterogeneous Computing Systems</atitle><jtitle>IEEE transactions on parallel and distributed systems</jtitle><stitle>TPDS</stitle><date>2008-12-01</date><risdate>2008</risdate><volume>19</volume><issue>12</issue><spage>1671</spage><epage>1682</epage><pages>1671-1682</pages><issn>1045-9219</issn><eissn>1558-2183</eissn><coden>ITDSEO</coden><abstract>Resource management systems (RMS) are an important component in heterogeneous computing (HC) systems. One of the jobs of an RMS is the mapping of arriving tasks onto the machines of the HC system. Many different mapping heuristics have been proposed in recent years. However, most of these heuristics suffer from several limitations. One of these limitations is the performance degradation that results from using outdated global information about the status of all machines in the HC system. This paper proposes several heuristics which address this limitation by only requiring partial information in making the mapping decisions. These heuristics utilize the solution to a linear programming (LP) problem which maximizes the system capacity. Simulation results show that our heuristics perform very competitively while requiring dramatically less information.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TPDS.2008.59</doi><tpages>12</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 1045-9219
ispartof IEEE transactions on parallel and distributed systems, 2008-12, Vol.19 (12), p.1671-1682
issn 1045-9219
1558-2183
language eng
recordid cdi_proquest_miscellaneous_875054740
source IEEE Electronic Library (IEL)
subjects Affinity
Availability
Computation
Computational modeling
Computer applications
Computer networks
Computer simulation
Degradation
distributed systems
heterogeneous processors
Heuristic
Linear programming
load balancing
Load management
Mapping
Processor scheduling
Queueing analysis
queueing theory
Resource management
Resources management
Scheduling
Tasks
title Linear Programming-Based Affinity Scheduling of Independent Tasks on Heterogeneous Computing Systems
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-19T22%3A52%3A12IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Linear%20Programming-Based%20Affinity%20Scheduling%20of%20Independent%20Tasks%20on%20Heterogeneous%20Computing%20Systems&rft.jtitle=IEEE%20transactions%20on%20parallel%20and%20distributed%20systems&rft.au=Al-Azzoni,%20I.&rft.date=2008-12-01&rft.volume=19&rft.issue=12&rft.spage=1671&rft.epage=1682&rft.pages=1671-1682&rft.issn=1045-9219&rft.eissn=1558-2183&rft.coden=ITDSEO&rft_id=info:doi/10.1109/TPDS.2008.59&rft_dat=%3Cproquest_RIE%3E34441305%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=912283149&rft_id=info:pmid/&rft_ieee_id=4492769&rfr_iscdi=true