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dc.contributor.authorRamos Garea, Sabela
dc.contributor.authorTaboada, Guillermo L.
dc.contributor.authorExpósito, Roberto R.
dc.contributor.authorTouriño, Juan
dc.date.accessioned2018-11-06T16:42:30Z
dc.date.available2018-11-06T16:42:30Z
dc.date.issued2015-04-22
dc.identifier.citationRamos, S., Taboada, G. L., Expósito, R. R., & Touriño, J. (2015). Nonblocking collectives for scalable Java communications. Concurrency and Computation: Practice and Experience, 27(5), 1169-1187.es_ES
dc.identifier.issn1532-0626
dc.identifier.issn1532-0634
dc.identifier.urihttp://hdl.handle.net/2183/21239
dc.descriptionThis is the peer reviewed version of the following article: Ramos, S., Taboada, G. L., Expósito, R. R., & Touriño, J. (2015). Nonblocking collectives for scalable Java communications. Concurrency and Computation: Practice and Experience, 27(5), 1169-1187, which has been published in final form at https://doi.org/10.1002/cpe.3279. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.es_ES
dc.description.abstract[Abstract] This paper presents a Java implementation of the recently published MPI 3.0 nonblocking message passing collectives in order to analyze and assess the feasibility of taking advantage of these operations in shared memory systems using Java. Nonblocking collectives aim to exploit the overlapping between computation and communication for collective operations to increase scalability of message passing codes, as it has been carried out for nonblocking point‐to‐point primitives. This scalability has become crucial not only for clusters but also for shared memory systems because of the current trend of increasing the number of cores per chip, which is leading to the generalization of multi‐core and many‐core processors. Message passing libraries based on remote direct memory access, thread‐based progression, or implementing pure multi‐threading shared memory support could potentially benefit from the lack of imposed synchronization by nonblocking collectives. But, although the distributed memory scenario has been well studied, the shared memory one has not been tackled yet. Hence, nonblocking collectives support has been included in FastMPJ, a Message Passing in Java (MPJ) implementation, and evaluated on a representative shared memory system, obtaining significant improvements because of overlapping and lack of implicit synchronization, and with barely any overhead imposed over common blocking operations.es_ES
dc.description.sponsorshipMinisterio de Ciencia e Innovación; TIN2010-16735es_ES
dc.description.sponsorshipXunta de Galicia; CN2012/211es_ES
dc.description.sponsorshipXunta de Galicia; GRC2013/055es_ES
dc.language.isoenges_ES
dc.publisherJohn Wiley & Sons Ltd.es_ES
dc.relation.urihttps://doi.org/10.1002/cpe.3279es_ES
dc.subjectCollective operationses_ES
dc.subjectJava multi‐threadinges_ES
dc.subjectMessage Passing in Java (MPJ)es_ES
dc.subjectMPI 3.0es_ES
dc.subjectNonblocking collectiveses_ES
dc.subjectShared memory architectureses_ES
dc.titleNonblocking collectives for scalable Java communicationses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleConcurrency and Computation: Practice & Experiencees_ES
UDC.volume27es_ES
UDC.issue5es_ES
UDC.startPage1169es_ES
UDC.endPage1187es_ES
dc.identifier.doi10.1002/cpe.3279


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