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DVFS-control techniques for dense linear algebra operations on multi-core processors

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DVFS-control techniques for dense linear algebra operations on multi-core processors

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Nombre: 10.1007_s00450-01 ...
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dc.contributor.author Alonso-Jordá, Pedro es_ES
dc.contributor.author Dolz Zaragozá, Manuel Francisco es_ES
dc.contributor.author Igual, Francisco D. es_ES
dc.contributor.author Mayo, Rafael es_ES
dc.contributor.author Quintana Ortí, Enrique Salvador es_ES
dc.date.accessioned 2015-12-30T08:53:23Z
dc.date.available 2015-12-30T08:53:23Z
dc.date.issued 2012-11
dc.identifier.issn 1865-2034
dc.identifier.uri http://hdl.handle.net/10251/59290
dc.description.abstract [EN] This paper analyzes the impact on power con- sumption of two DVFS-control strategies when applied to the execution of dense linear algebra operations on multi- core processors. The strategies considered here, prototyped as the Slack Reduction Algorithm (SRA) and the Race-to- Idle Algorithm (RIA), adjust the operation frequency of the cores during execution of a collection of tasks (in which many dense linear algebra algorithms can be decomposed) with a very different approach to save energy. A power- aware simulator, in charge of scheduling the execution of tasks to processor cores, is employed to evaluate the perfor- mance benefits of these power-control policies for two ref- erence algorithms for the LU factorization, a key operation for the solution of linear systems of equations. es_ES
dc.description.sponsorship The authors from Univ. Jaume I were supported by project CICYT TIN2008-06570-C04 and FEDER.
dc.language Inglés es_ES
dc.publisher Springer Verlag (Germany) es_ES
dc.relation.ispartof Computer Science - Research and Development es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Dense linear algebra es_ES
dc.subject Power consumption es_ES
dc.subject Multi-core processors es_ES
dc.subject DVFS es_ES
dc.subject.classification CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title DVFS-control techniques for dense linear algebra operations on multi-core processors es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s00450-011-0188-7
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//TIN2008-06570-C04-01/ES/CONSTRUCCION Y OPTIMIZACION AUTOMATICAS DE BIBLIOTECAS PARALELAS DE COMPUTACION CIENTIFICA - UJI/
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//TIN2008-06570-C04-04/ES/CONSTRUCCION Y OPTIMIZACION AUTOMATICAS DE BIBLIOTECAS PARALELAS DE COMPUTACION CIENTIFICA - UA/
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//TIN2008-06570-C04-02/ES/CONSTRUCCION Y OPTIMIZACION AUTOMATICAS DE BIBLIOTECAS PARALELAS DE COMPUTACION CIENTIFICA - UM/
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Alonso-Jordá, P.; Dolz Zaragozá, MF.; Igual, FD.; Mayo, R.; Quintana Ortí, ES. (2012). DVFS-control techniques for dense linear algebra operations on multi-core processors. Computer Science - Research and Development. 27(4):289-298. https://doi.org/10.1007/s00450-011-0188-7 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1007/s00450-011-0188-7 es_ES
dc.description.upvformatpinicio 289 es_ES
dc.description.upvformatpfin 298 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 27 es_ES
dc.description.issue 4 es_ES
dc.relation.senia 232835 es_ES
dc.contributor.funder Ministerio de Ciencia e Innovación
dc.description.references Albers S (2010) Energy-efficient algorithms. Commun ACM 53:86–96 es_ES
dc.description.references Dongarra J et al. (2011) The international ExaScale software project roadmap. Int J High Perform Comput Appl, 25(1):3–60 es_ES
dc.description.references Duranton M et al. (2010) The HiPEAC vision. Available from http://www.hipeac.net/roadmap es_ES
dc.description.references Feng W, Feng X, Ce R (2008) Green supercomputing comes of age. IT Prof 10(1):17–23 es_ES
dc.description.references Gruber R, Keller V (2010) One joule per GFlop for BLAS2 now! In: Simos TE, Psihoyios G, Tsitouras C (eds) AIP conf proceedings, vol 1281. American Institute of Physics, College Park, pp 1321–1324 es_ES
dc.description.references Ludwig T (2010) Editorial for the first international conference on energy-aware high performance computing. Comput Sci Res Dev 25(3):123–124 es_ES
dc.description.references Golub GH, Van Loan CF (1996) Matrix computations, 3rd edn. The Johns Hopkins University Press, Baltimore es_ES
dc.description.references Van Zee FG (2009) libflame: the complete reference. www.lulu.com es_ES
dc.description.references Anderson E, Bai Z, Bischof C, Blackford LS, Demmel J, Dongarra JJ, Croz Du J, Hammarling S, Greenbaum A, McKenney A, Sorensen D (1999) LAPACK users’ guide, 3rd edn. SIAM, Philadelphia es_ES
dc.description.references Hsu C, Feng W (2005) A feasibility analysis of power awareness in commodity-based high-performance clusters. In: Cluster 2005 es_ES
dc.description.references Quintana-Ortí ES, van de Geijn RA (2008) Updating an LU factorization with pivoting. ACM Trans Math Softw 35(2):11:1–11:16 es_ES
dc.description.references Quintana-Ortí G, Quintana-Ortí ES, van de Geijn RA, Van Zee FG, Chan E (2009) Programming matrix algorithms-by-blocks for thread-level parallelism. ACM Trans Math Softw 36(3):14:1–14:26 es_ES
dc.description.references Freeh VW, Lowenthal DK, Pan F, Kappiah N, Springer R, Rountree BL, Femal ME (2007) Analyzing the energy-time trade-off in high-performance computing applications. IEEE Trans Parallel Distrib Syst 18:835–848 es_ES
dc.description.references King D, Ahmad I, Sheikh HF (2010) Stretch and compress based re-scheduling techniques for minimizing the execution times of DAGs on multi-core processors under energy constraints. In: International conference on green computing. IEEE Press, New York, pp 49–60 es_ES
dc.description.references Palli K (2005) Scheduling dags for minimum finish time and power consumption on heterogeneous processors. Master’s thesis, Albers University, Albers, AL es_ES
dc.description.references Shaffer LR, Ritter JB, Meyer WL (1965) The critical-path method. McGraw-Hill, New York es_ES
dc.description.references Alonso P, Dolz MF, Mayo R, Quintana-Ortí ES (2011) Improving power efficiency of dense linear algorithms on multi-core processors via slack control. Proceedings of the 2011 international conference on high performance computing & simulation (HPCS 2011). IEE Catzlog Number. CFP1178H-CDR, pp. 463–470 es_ES
dc.description.references Alonso P, Dolz MF, Mayo R, Quintana-Ortí ES (2011) Energy-aware scheduling of dense linear algebra operations on multi-core processors. Technical report 2011-04-01, Depto. de Ingeniería y Ciencia de los Computadores, Universitat Jaume I, April 2011 es_ES
dc.description.references Li R, Huang HC (2007) List scheduling for jobs with arbitrary release times and similar lengths. J Sched 10(6):365–373 es_ES
dc.description.references Mtibaa A, Ouni B, Abid M (2007) An efficient list scheduling algorithm for time placement problem. Comput Electr Eng 33(4):285–298 es_ES


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