Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/90122

Registo completo
Campo DCValorIdioma
dc.contributor.authorSilva, Rui António Sabino Castiçopor
dc.contributor.authorSobral, João Luís Ferreirapor
dc.date.accessioned2024-03-27T09:00:32Z-
dc.date.issued2022-06-
dc.identifier.isbn978-3-031-06155-4-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://hdl.handle.net/1822/90122-
dc.description.abstractJava streams enable an easy-to-use functional-like programming style that transparently supports parallel execution. This paper presents an approach that improves the performance of stream-based Java applications. The approach enables the effective usage of Java for HPC applications, due to data locality improvements (i.e., support for efficient data layouts), without losing the object-oriented view of data in the code. The approach extends the Java collections API to hide additional details concerning the data layout, enabling the transparent use of more memory-friendly data layouts. The enhanced Java Collection API enables an easy adaptation of existing Java codes making those Java codes suitable for HPC. Performance results show that improving the data locality can provide a two-fold performance gain in sequential stream applications, which translated into a similar gain over parallel stream implementations. Moreover, the performance is comparable to similar C implementations using OpenMP.por
dc.description.sponsorship- This work has been supported by FCT -Fundacao para a Ciencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. The evaluation used the computing infra-structure of the project Search-ON2: Revitalization of HPC infrastructure of UMinho, (NORTE-07-0162-FEDER-000086), co-funded by the North Portugal Regional Operational Programme (ON.2-O Novo Norte), under the National Strategic Reference Framework (NSRF), through the European Regional Development Fund (ERDF).por
dc.language.isoengpor
dc.publisherSpringerpor
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00319%2F2020/PTpor
dc.relationNORTE-07-0162-FEDER-000086por
dc.rightsrestrictedAccesspor
dc.subjectJava parallel streamspor
dc.subjectData layoutpor
dc.subjectData localitypor
dc.titleHigh performance computing with java streamspor
dc.typeconferencePaperpor
dc.peerreviewedyespor
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007/978-3-031-06156-1_2por
oaire.citationStartPage17por
oaire.citationEndPage28por
oaire.citationVolume13098por
dc.date.updated2024-03-25T12:18:23Z-
dc.identifier.eissn1611-3349-
dc.identifier.doi10.1007/978-3-031-06156-1_2por
dc.date.embargo10000-01-01-
dc.identifier.eisbn978-3-031-06156-1-
dc.subject.wosScience & Technology-
sdum.export.identifier14731-
sdum.journalLecture Notes in Computer Science (LNCS)por
sdum.conferencePublicationEuropean Conference on Parallel Processing - Euro-Par 2021por
sdum.bookTitleEuro-Par 2021: Parallel Processing Workshopspor
Aparece nas coleções:CAlg - Artigos em livros de atas/Papers in proceedings

Ficheiros deste registo:
Ficheiro Descrição TamanhoFormato 
Locality2021LNCS.pdf
Acesso restrito!
475,03 kBAdobe PDFVer/Abrir

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID