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Automatic mapping of parallel applications on multicore architectures using the Servet benchmark suite
dc.contributor.author | González-Domínguez, Jorge | |
dc.contributor.author | Taboada, Guillermo L. | |
dc.contributor.author | Fraguela, Basilio B. | |
dc.contributor.author | Martín, María J. | |
dc.contributor.author | Touriño, Juan | |
dc.date.accessioned | 2019-02-07T18:09:30Z | |
dc.date.available | 2019-02-07T18:09:30Z | |
dc.date.issued | 2012-03 | |
dc.identifier.citation | GONZÁLEZ-DOMÍNGUEZ, Jorge, et al. Automatic mapping of parallel applications on multicore architectures using the servet benchmark suite. Computers & Electrical Engineering, 2012, vol. 38, no 2, p. 258-269. | es_ES |
dc.identifier.issn | 0045-7906 | |
dc.identifier.issn | 1879-0755 | |
dc.identifier.uri | http://hdl.handle.net/2183/21693 | |
dc.description | This is a post-peer-review, pre-copyedit version of an article published in Computers & Electrical Engineering. The final authenticated version is available online at: https://doi.org/10.1016/j.compeleceng.2011.12.007 | es_ES |
dc.description.abstract | [Abstract] 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. | es_ES |
dc.description.sponsorship | Ministerio de Ciencia e Innovación; TIN2010-16735 | es_ES |
dc.description.sponsorship | Ministerio de Educación; FPU; AP2008-01578 | es_ES |
dc.description.sponsorship | Xunta de Galicia; INCITE08PXIB105161PR | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Pergamon Press | es_ES |
dc.relation.uri | https://doi.org/10.1016/j.compeleceng.2011.12.007 | es_ES |
dc.rights | Atribución-NoComercial-SinDerivadas 3.0 España | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.subject | Multicore systems | es_ES |
dc.subject | Multicore clusters | es_ES |
dc.subject | Algorithms | es_ES |
dc.subject | Parallel applications | es_ES |
dc.subject | Parallel programming | es_ES |
dc.title | Automatic mapping of parallel applications on multicore architectures using the Servet benchmark suite | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Computers & Electrical Engineering | es_ES |
UDC.volume | 38 | es_ES |
UDC.issue | 2 | es_ES |
UDC.startPage | 258 | es_ES |
UDC.endPage | 269 | es_ES |
dc.identifier.doi | 10.1016/j.compeleceng.2011.12.007 |
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