Efficient Master/Worker Parallel Discrete Event Simulation
The master/worker (MW) paradigm can be used to implement parallel discrete event simulations (PDES) on metacomputing systems. MW PDES applications incur overheads not found in conventional PDES executions executing on tightly coupled machines. We introduce four techniques for reducing these overhead...
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Computing methodologies
> Modeling and simulation
> Model development and analysis
> Model verification and validation
Computing methodologies
> Modeling and simulation
> Model development and analysis
> Modeling methodologies
Computing methodologies
> Modeling and simulation
> Simulation types and techniques
> Discrete-event simulation
Computing methodologies
> Modeling and simulation
> Simulation types and techniques
> Massively parallel and high-performance simulations
Software and its engineering
> Software notations and tools
> General programming languages
> Language types
> Concurrent programming languages
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| creator | Park, Alfred Fujimoto, Richard M. |
| description | The master/worker (MW) paradigm can be used to implement parallel discrete event simulations (PDES) on metacomputing systems. MW PDES applications incur overheads not found in conventional PDES executions executing on tightly coupled machines. We introduce four techniques for reducing these overheads on public resource and desktop grid infrastructures Work unit caching, pipelined state updates, expedited message delivery, and adaptive work unit scheduling mechanisms are described that provide significant reduction in overall overhead when used in tandem. We present performance results showing that an optimized MW PDES system can exhibit performance comparable to a traditional PDES system for a queueing network and a particle physics simulation. |
| doi_str_mv | 10.1109/PADS.2009.9 |
| format | Conference Proceeding |
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MW PDES applications incur overheads not found in conventional PDES executions executing on tightly coupled machines. We introduce four techniques for reducing these overheads on public resource and desktop grid infrastructures Work unit caching, pipelined state updates, expedited message delivery, and adaptive work unit scheduling mechanisms are described that provide significant reduction in overall overhead when used in tandem. We present performance results showing that an optimized MW PDES system can exhibit performance comparable to a traditional PDES system for a queueing network and a particle physics simulation.</description><identifier>ISSN: 1087-4097</identifier><identifier>ISBN: 9780769537139</identifier><identifier>ISBN: 0769537138</identifier><identifier>DOI: 10.1109/PADS.2009.9</identifier><language>eng</language><publisher>Washington, DC, USA: IEEE Computer Society</publisher><subject>Cache storage ; caching ; Computational modeling ; Computing methodologies -- Concurrent computing methodologies -- Concurrent programming languages ; Computing methodologies -- Modeling and simulation -- Model development and analysis ; Computing methodologies -- Modeling and simulation -- Model development and analysis -- Model verification and validation ; Computing methodologies -- Modeling and simulation -- Model development and analysis -- Modeling methodologies ; Computing methodologies -- Modeling and simulation -- Simulation types and techniques -- Discrete-event simulation ; Computing methodologies -- Modeling and simulation -- Simulation types and techniques -- Massively parallel and high-performance simulations ; Concurrent computing ; Conferences ; conservative synchronization ; desktop grids ; Discrete event simulation ; Distributed computing ; Fault tolerance ; grid computing ; Master/worker ; metacomputing ; Packaging ; parallel discrete event simulation ; PDES ; Processor scheduling ; simulation ; Software and its engineering -- Software notations and tools -- General programming languages -- Language types -- Concurrent programming languages ; Software and its engineering -- Software organization and properties -- Software system structures -- Distributed systems organizing principles ; USA Councils ; volunteer computing</subject><ispartof>2009 ACM/IEEE/SCS 23rd Workshop on Principles of Advanced and Distributed Simulation, 2009, p.145-152</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5158330$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>310,311,781,785,790,791,2059,27930,54925</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5158330$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Park, Alfred</creatorcontrib><creatorcontrib>Fujimoto, Richard M.</creatorcontrib><title>Efficient Master/Worker Parallel Discrete Event Simulation</title><title>2009 ACM/IEEE/SCS 23rd Workshop on Principles of Advanced and Distributed Simulation</title><addtitle>PADS</addtitle><description>The master/worker (MW) paradigm can be used to implement parallel discrete event simulations (PDES) on metacomputing systems. 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Fujimoto, Richard M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a239t-1b58e73cd7547032fffc8383d1ce7db743059440ee120972e13b4fca1784bd233</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Cache storage</topic><topic>caching</topic><topic>Computational modeling</topic><topic>Computing methodologies -- Concurrent computing methodologies -- Concurrent programming languages</topic><topic>Computing methodologies -- Modeling and simulation -- Model development and analysis</topic><topic>Computing methodologies -- Modeling and simulation -- Model development and analysis -- Model verification and validation</topic><topic>Computing methodologies -- Modeling and simulation -- Model development and analysis -- Modeling methodologies</topic><topic>Computing methodologies -- Modeling and simulation -- Simulation types and techniques -- Discrete-event simulation</topic><topic>Computing methodologies -- Modeling and simulation -- Simulation types and techniques -- Massively parallel and high-performance simulations</topic><topic>Concurrent computing</topic><topic>Conferences</topic><topic>conservative synchronization</topic><topic>desktop grids</topic><topic>Discrete event simulation</topic><topic>Distributed computing</topic><topic>Fault tolerance</topic><topic>grid computing</topic><topic>Master/worker</topic><topic>metacomputing</topic><topic>Packaging</topic><topic>parallel discrete event simulation</topic><topic>PDES</topic><topic>Processor scheduling</topic><topic>simulation</topic><topic>Software and its engineering -- Software notations and tools -- General programming languages -- Language types -- Concurrent programming languages</topic><topic>Software and its engineering -- Software organization and properties -- Software system structures -- Distributed systems organizing principles</topic><topic>USA Councils</topic><topic>volunteer computing</topic><toplevel>online_resources</toplevel><creatorcontrib>Park, Alfred</creatorcontrib><creatorcontrib>Fujimoto, Richard M.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Park, Alfred</au><au>Fujimoto, Richard M.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Efficient Master/Worker Parallel Discrete Event Simulation</atitle><btitle>2009 ACM/IEEE/SCS 23rd Workshop on Principles of Advanced and Distributed Simulation</btitle><stitle>PADS</stitle><date>2009-06-22</date><risdate>2009</risdate><spage>145</spage><epage>152</epage><pages>145-152</pages><issn>1087-4097</issn><isbn>9780769537139</isbn><isbn>0769537138</isbn><abstract>The master/worker (MW) paradigm can be used to implement parallel discrete event simulations (PDES) on metacomputing systems. MW PDES applications incur overheads not found in conventional PDES executions executing on tightly coupled machines. We introduce four techniques for reducing these overheads on public resource and desktop grid infrastructures Work unit caching, pipelined state updates, expedited message delivery, and adaptive work unit scheduling mechanisms are described that provide significant reduction in overall overhead when used in tandem. We present performance results showing that an optimized MW PDES system can exhibit performance comparable to a traditional PDES system for a queueing network and a particle physics simulation.</abstract><cop>Washington, DC, USA</cop><pub>IEEE Computer Society</pub><doi>10.1109/PADS.2009.9</doi><tpages>8</tpages></addata></record> |
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| identifier | ISSN: 1087-4097 |
| ispartof | 2009 ACM/IEEE/SCS 23rd Workshop on Principles of Advanced and Distributed Simulation, 2009, p.145-152 |
| issn | 1087-4097 |
| language | eng |
| recordid | cdi_ieee_primary_5158330 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Cache storage caching Computational modeling Computing methodologies -- Concurrent computing methodologies -- Concurrent programming languages Computing methodologies -- Modeling and simulation -- Model development and analysis Computing methodologies -- Modeling and simulation -- Model development and analysis -- Model verification and validation Computing methodologies -- Modeling and simulation -- Model development and analysis -- Modeling methodologies Computing methodologies -- Modeling and simulation -- Simulation types and techniques -- Discrete-event simulation Computing methodologies -- Modeling and simulation -- Simulation types and techniques -- Massively parallel and high-performance simulations Concurrent computing Conferences conservative synchronization desktop grids Discrete event simulation Distributed computing Fault tolerance grid computing Master/worker metacomputing Packaging parallel discrete event simulation PDES Processor scheduling simulation Software and its engineering -- Software notations and tools -- General programming languages -- Language types -- Concurrent programming languages Software and its engineering -- Software organization and properties -- Software system structures -- Distributed systems organizing principles USA Councils volunteer computing |
| title | Efficient Master/Worker Parallel Discrete Event Simulation |
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