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An efficient implementation of parallel simulated annealing algorithm in GPUs
dc.contributor.author | Ferreiro Ferreiro, Ana María | |
dc.contributor.author | García Rodríguez, José Antonio | |
dc.contributor.author | López Salas, José Germán | |
dc.contributor.author | Vázquez, Carlos | |
dc.date.accessioned | 2024-07-17T09:37:58Z | |
dc.date.available | 2024-07-17T09:37:58Z | |
dc.date.issued | 2012-09-26 | |
dc.identifier.citation | Ferreiro, A.M., García, J.A., López-Salas, J.G. et al. An efficient implementation of parallel simulated annealing algorithm in GPUs. J Glob Optim 57, 863–890 (2013). https://doi.org/10.1007/s10898-012-9979-z | es_ES |
dc.identifier.issn | 0925-5001 | |
dc.identifier.uri | http://hdl.handle.net/2183/38098 | |
dc.description | ©2012 This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s10898-012-9979-z | es_ES |
dc.description.abstract | [Abstract]: In this work we propose a highly optimized version of a simulated annealing (SA) algorithm adapted to the more recently developed graphic processor units (GPUs). The programming has been carried out with compute unified device architecture (CUDA) toolkit, specially designed for Nvidia GPUs. For this purpose, efficient versions of SA have been first analyzed and adapted to GPUs. Thus, an appropriate sequential SA algorithm has been developed as starting point. Next, a straightforward asynchronous parallel version has been implemented and then a specific and more efficient synchronous version has been developed. A wide appropriate benchmark to illustrate the performance properties of the implementation has been considered. Among all tests, a classical sample problem provided by the minimization of the normalized Schwefel function has been selected to compare the behavior of the sequential, asynchronous and synchronous versions, the last one being more advantageous in terms of balance between convergence, accuracy and computational cost. Also the implementation of a hybrid method combining SA with a local minimizer method has been developed. Note that the generic feature of the SA algorithm allows its application in a wide set of real problems arising in a large variety of fields, such as biology, physics, engineering, finance and industrial processes. | es_ES |
dc.description.sponsorship | This work is partially supported by I-Math Consolider Project (Reference: COMPC6-0393), by MICINN (MTM2010-21135-C02-01) and by Xunta de Galicia (Grant CN2011/004 cofunded with FEDER funds). The authors also acknowledge some ideas suggested by J. L. Fernández (Autonomous University of Madrid). | es_ES |
dc.description.sponsorship | Xunta de Galicia; CN2011/004 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Springer | es_ES |
dc.relation | info:eu-repo/grantAgreement/MICINN/Plan Nacional de I+D+i 2008-2011/MTM2010-21135-C02-01/ES/MODELOS, ANALISIS MATEMATICO Y RESOLUCION NUMERICA DE ALGUNOS PROBLEMAS EN CIENCIA E INGENIERIA BASADOS EN EDPS | es_ES |
dc.relation.uri | https://doi.org/10.1007/s10898-012-9979-z | es_ES |
dc.subject | Global optimization | es_ES |
dc.subject | Simulated annealing | es_ES |
dc.subject | Parallel computing | es_ES |
dc.subject | GPUs | es_ES |
dc.subject | CUDA | es_ES |
dc.title | An efficient implementation of parallel simulated annealing algorithm in GPUs | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | Journal of Global Optimization | es_ES |
UDC.volume | 57 | es_ES |
UDC.startPage | 863 | es_ES |
UDC.endPage | 890 | es_ES |
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