Automatic mapping of parallel applications on multicore architectures using the Servet benchmark suite
[Display omitted] ► Multicore systems require new mapping policies to make the most of the architecture. ► An automatic mapping based on Servet is proposed. ► Servet is a benchmark suite that obtains relevant hardware parameters of clusters. ► Results show a significant improvement of performance of...
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| Vydáno v: | Computers & electrical engineering Ročník 38; číslo 2; s. 258 - 269 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier Ltd
01.03.2012
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| ISSN: | 0045-7906, 1879-0755 |
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| Abstract | [Display omitted]
► Multicore systems require new mapping policies to make the most of the architecture. ► An automatic mapping based on Servet is proposed. ► Servet is a benchmark suite that obtains relevant hardware parameters of clusters. ► Results show a significant improvement of performance of parallel applications. ► The mapping technique proposed does not require source code modifications.
Servet is a suite of benchmarks focused on detecting a set of parameters with high influence on the overall performance of multicore systems. These parameters can be used for autotuning codes to increase their performance on multicore clusters. Although Servet has been proved to detect accurately cache hierarchies, bandwidths and bottlenecks in memory accesses, as well as the communication overhead among cores, up to now the impact of the use of this information on application performance optimization has not been assessed. This paper presents a novel algorithm that automatically uses Servet for mapping parallel applications on multicore systems and analyzes its impact on three testbeds using three different parallel programming models: message-passing, shared memory and partitioned global address space (PGAS). Our results show that a suitable mapping policy based on the data provided by this tool can significantly improve the performance of parallel applications without source code modification. |
|---|---|
| AbstractList | [Display omitted]
► Multicore systems require new mapping policies to make the most of the architecture. ► An automatic mapping based on Servet is proposed. ► Servet is a benchmark suite that obtains relevant hardware parameters of clusters. ► Results show a significant improvement of performance of parallel applications. ► The mapping technique proposed does not require source code modifications.
Servet is a suite of benchmarks focused on detecting a set of parameters with high influence on the overall performance of multicore systems. These parameters can be used for autotuning codes to increase their performance on multicore clusters. Although Servet has been proved to detect accurately cache hierarchies, bandwidths and bottlenecks in memory accesses, as well as the communication overhead among cores, up to now the impact of the use of this information on application performance optimization has not been assessed. This paper presents a novel algorithm that automatically uses Servet for mapping parallel applications on multicore systems and analyzes its impact on three testbeds using three different parallel programming models: message-passing, shared memory and partitioned global address space (PGAS). Our results show that a suitable mapping policy based on the data provided by this tool can significantly improve the performance of parallel applications without source code modification. Servet is a suite of benchmarks focused on detecting a set of parameters with high influence on the overall performance of multicore systems. These parameters can be used for autotuning codes to increase their performance on multicore clusters. Although Servet has been proved to detect accurately cache hierarchies, bandwidths and bottlenecks in memory accesses, as well as the communication overhead among cores, up to now the impact of the use of this information on application performance optimization has not been assessed. This paper presents a novel algorithm that automatically uses Servet for mapping parallel applications on multicore systems and analyzes its impact on three testbeds using three different parallel programming models: message-passing, shared memory and partitioned global address space (PGAS). Our results show that a suitable mapping policy based on the data provided by this tool can significantly improve the performance of parallel applications without source code modification. |
| Author | Taboada, Guillermo L. Martín, María J. Touriño, Juan González-Domínguez, Jorge Fraguela, Basilio B. |
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| Cites_doi | 10.1145/1088149.1088202 10.1016/S0167-8191(00)00087-9 10.1109/JPROC.2004.840301 10.1109/SC.2000.10024 10.1145/1542275.1542344 10.1016/j.compeleceng.2011.05.012 10.1145/331532.331555 10.1016/j.compeleceng.2007.09.007 10.1109/PACT.2009.11 10.1109/JPROC.2004.840306 10.1145/1183401.1183451 10.1109/JPROC.2004.840444 10.1109/PDP.2010.67 10.1109/IPDPS.2010.5470442 10.1109/IPDPS.2010.5470358 |
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| References_xml | – reference: Fraguela BB, Voronenko Y, Püschel M. Automatic tuning of discrete fourier transforms driven by analytical modeling. In: Proceedings of 18th international conference on parallel architectures and compilation techniques (PACT’09). Raleigh, NC, USA; 2009. p. 271–80. – reference: Mercier G, Clêt-Ortega J. Towards an efficient process placement policy for MPI applications in multicore environments. In: Proceedings of 16th European PVM/MPI users’, group meeting (EuroPVM/MPI’09), vol. 5759 of lecture notes in computer science. Espoo, Finland; 2009. p. 104–15. – reference: Message Passing Interface Forum. – reference: The Servet Benchmark Suite. – reference: Sistare S, Vandevaart R, Loh E. Optimization of MPI collectives on clusters of large-scale SMPs. In: Proceedings of 12th ACM/IEEE conference on supercomputing (SC’99). Portland, OR, USA; 1999. p. 23–36. – reference: Vadhiyar SS, Fagg GE, Dongarra JJ. Automatically tuned collective communications. 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► Multicore systems require new mapping policies to make the most of the architecture. ► An automatic mapping based on Servet is proposed. ►... Servet is a suite of benchmarks focused on detecting a set of parameters with high influence on the overall performance of multicore systems. These parameters... |
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| Title | Automatic mapping of parallel applications on multicore architectures using the Servet benchmark suite |
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