A New Task Graph Model for Mapping Message Passing Applications
The exploitation of parallelism in a message passing platform implies a previous modeling phase of the parallel application as a task graph, which properly reflects its temporal behavior. In this paper, we analyze the classical task graph models of the literature and their drawbacks when modeling me...
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Veröffentlicht in: | IEEE transactions on parallel and distributed systems 2007-12, Vol.18 (12), p.1740-1753 |
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container_title | IEEE transactions on parallel and distributed systems |
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creator | Roig, C. Ripoll, A. Guirado, F. |
description | The exploitation of parallelism in a message passing platform implies a previous modeling phase of the parallel application as a task graph, which properly reflects its temporal behavior. In this paper, we analyze the classical task graph models of the literature and their drawbacks when modeling message passing programs with an arbitrary task structure. We define a new task graph model called temporal task interaction graph (TTIG) that integrates the classical models used in the literature. The TTIG allows us to explicitly capture the ability of concurrency of adjacent tasks for applications where adjacent tasks can communicate at any point inside them. A mapping strategy is developed from this model, which minimizes the expected execution time by properly exploiting task parallelism. The effectiveness of this approach has been proved in different experimentation scopes for a wide range of message passing applications. |
doi_str_mv | 10.1109/TPDS.2007.1117 |
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In this paper, we analyze the classical task graph models of the literature and their drawbacks when modeling message passing programs with an arbitrary task structure. We define a new task graph model called temporal task interaction graph (TTIG) that integrates the classical models used in the literature. The TTIG allows us to explicitly capture the ability of concurrency of adjacent tasks for applications where adjacent tasks can communicate at any point inside them. A mapping strategy is developed from this model, which minimizes the expected execution time by properly exploiting task parallelism. 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The effectiveness of this approach has been proved in different experimentation scopes for a wide range of message passing applications.</description><subject>Application software</subject><subject>Clustering algorithms</subject><subject>Computer Society</subject><subject>Concurrency</subject><subject>Concurrent computing</subject><subject>Graphs</subject><subject>High-speed networks</subject><subject>Mapping</subject><subject>mapping algorithms</subject><subject>Message passing</subject><subject>Microprocessors</subject><subject>modelling message-passing programs</subject><subject>Parallel processing</subject><subject>Platforms</subject><subject>program behaviour</subject><subject>Scientific computing</subject><subject>static mapping</subject><subject>Strategy</subject><subject>task concurrency</subject><subject>Task graphs</subject><subject>Tasks</subject><subject>Temporal logic</subject><subject>Workstations</subject><issn>1045-9219</issn><issn>1558-2183</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNqF0T1PwzAQBmALgUQprCwsFgNMKf5M7AlVBQpSC5Uos-U6l5KSJsFuhfj3OCpiYIDJd9JzJ59ehE4pGVBK9NV8dvM8YIRksaXZHupRKVXCqOL7sSZCJppRfYiOQlgRQoUkooeuh_gRPvDchjc89rZ9xdMmhwoXjcdT27ZlvcRTCMEuAc9sCF0_bNuqdHZTNnU4RgeFrQKcfL999HJ3Ox_dJ5On8cNoOEkcV3STgEwhBel4zpmyzEnHpCrcwhYpd5SAVTwnTCzyVIHLSC7ydKEz5bKIVKY176PL3d7WN-9bCBuzLoODqrI1NNtgNOEpZxkV_0qlSKoyJVSUF39KLgRX8fsRnv-Cq2br63iv0ZQxwpXu0GCHnG9C8FCY1pdr6z8NJaYLyHQBmS4g0wUUB852AyUA_GDBpRZE8i-zaom1</recordid><startdate>20071201</startdate><enddate>20071201</enddate><creator>Roig, C.</creator><creator>Ripoll, A.</creator><creator>Guirado, F.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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In this paper, we analyze the classical task graph models of the literature and their drawbacks when modeling message passing programs with an arbitrary task structure. We define a new task graph model called temporal task interaction graph (TTIG) that integrates the classical models used in the literature. The TTIG allows us to explicitly capture the ability of concurrency of adjacent tasks for applications where adjacent tasks can communicate at any point inside them. A mapping strategy is developed from this model, which minimizes the expected execution time by properly exploiting task parallelism. The effectiveness of this approach has been proved in different experimentation scopes for a wide range of message passing applications.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TPDS.2007.1117</doi><tpages>14</tpages></addata></record> |
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subjects | Application software Clustering algorithms Computer Society Concurrency Concurrent computing Graphs High-speed networks Mapping mapping algorithms Message passing Microprocessors modelling message-passing programs Parallel processing Platforms program behaviour Scientific computing static mapping Strategy task concurrency Task graphs Tasks Temporal logic Workstations |
title | A New Task Graph Model for Mapping Message Passing Applications |
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