Exploiting controlled-grained parallelism in message-driven stream programs
With the increasing amount of parallelism obtainable on multicore platforms, stream programming has been proposed as an effective solution for exposing distributed parallelization. Nonetheless, a pressing demand of scheduling task and data parallelism in stream programming exists that can accomplish...
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| Vydáno v: | The Journal of supercomputing Ročník 70; číslo 1; s. 488 - 509 |
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| Jazyk: | angličtina |
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01.10.2014
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| ISSN: | 0920-8542, 1573-0484 |
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| Abstract | With the increasing amount of parallelism obtainable on multicore platforms, stream programming has been proposed as an effective solution for exposing distributed parallelization. Nonetheless, a pressing demand of scheduling task and data parallelism in stream programming exists that can accomplish robust multicore performance in the face of varying application characteristics. This paper addresses the problem of scheduling task and data parallelism in stream programming. We present StreamMDE, an asynchronous concurrency stream programming framework which offers a novel parallel programming model for scheduling task and data parallelism in the message-driven execution paradigm. A key property of this framework is exposing controlled-grained parallelism, which allows us to control the granularity of task and data parallelism in stream graph. Our empirical evaluation of StreamMDE shows that higher efficiency of mixed task and data parallelism in stream programming can be exploited with the appropriate granularity control. The framework bridges the gap between the parallel scale and the architecture of stream programs and facilitates in designing and coding stream features in different schedules. |
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| AbstractList | With the increasing amount of parallelism obtainable on multicore platforms, stream programming has been proposed as an effective solution for exposing distributed parallelization. Nonetheless, a pressing demand of scheduling task and data parallelism in stream programming exists that can accomplish robust multicore performance in the face of varying application characteristics. This paper addresses the problem of scheduling task and data parallelism in stream programming. We present StreamMDE, an asynchronous concurrency stream programming framework which offers a novel parallel programming model for scheduling task and data parallelism in the message-driven execution paradigm. A key property of this framework is exposing controlled-grained parallelism, which allows us to control the granularity of task and data parallelism in stream graph. Our empirical evaluation of StreamMDE shows that higher efficiency of mixed task and data parallelism in stream programming can be exploited with the appropriate granularity control. The framework bridges the gap between the parallel scale and the architecture of stream programs and facilitates in designing and coding stream features in different schedules. |
| Author | Su, Yan Shi, Feng Wei, Jin Tan, Hai Talpur, Shahnawaz |
| Author_xml | – sequence: 1 givenname: Yan surname: Su fullname: Su, Yan organization: Beijing Institute of Technology – sequence: 2 givenname: Feng surname: Shi fullname: Shi, Feng organization: Beijing Institute of Technology – sequence: 3 givenname: Shahnawaz surname: Talpur fullname: Talpur, Shahnawaz organization: Beijing Institute of Technology, Mehran University of Engineering and Technology, Jamshoro – sequence: 4 givenname: Jin surname: Wei fullname: Wei, Jin email: Jin.Springer@hotmail.com organization: Beijing Institute of Technology – sequence: 5 givenname: Hai surname: Tan fullname: Tan, Hai organization: Beijing Institute of Technology |
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| Cites_doi | 10.1145/635506.605428 10.1109/TCAD.2008.923415 10.1109/71.640018 10.1145/1015706.1015800 10.1016/j.jpdc.2004.03.006 10.1109/TC.1987.5009446 10.1109/MM.2006.45 10.1109/TSP.2002.800830 10.1109/TPDS.2011.308 10.1145/1168919.1168877 10.1007/3-540-45937-5_14 10.1109/5.97300 10.1145/1297105.1297043 10.1109/DATE.2008.4484886 10.1145/1064978.1065038 10.1145/2379776.2379780 10.1109/HIPC.2010.5713177 10.1145/956750.956814 10.1109/MC.2003.1220582 10.1007/978-3-642-30397-5_1 10.1145/1274971.1274987 10.1145/1854273.1854323 10.1145/165854.165874 10.1109/FMPC.1995.380446 10.1109/ICCIS.2013.421 10.1007/978-3-642-30397-5_3 |
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| Keywords | Multicore Stream programming Message-driven execution Controlled-grained parallelism C++11 |
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| Title | Exploiting controlled-grained parallelism in message-driven stream programs |
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