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Programming languages for data-Intensive HPC applications: A systematic mapping study

2020-03Journal article Restricted access
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dc.contributor.authorAmaral, Vasco
dc.contributor.authorNorberto, Beatriz
dc.contributor.authorGoulão, Miguel
dc.contributor.authorAldinucci, Marco
dc.contributor.authorBenkner, Siegfried
dc.contributor.authorBracciali, Andrea
dc.contributor.authorCarreira, Paulo
dc.contributor.authorCelms, Edgars
dc.contributor.authorCorreia, Luís
dc.contributor.authorGrelck, Clemens
dc.contributor.authorKaratza, Helen
dc.contributor.authorKessler, Christoph
dc.contributor.authorKilpatrick, Peter
dc.contributor.authorMartiniano, Hugo
dc.contributor.authorMavridis, Ilias
dc.contributor.authorPLLANA, Sabri
dc.contributor.authorRespicio, Ana
dc.contributor.authorSimão, José
dc.contributor.authorVeiga, Luís
dc.contributor.authorVisa, Ari Juha Eljas
dc.date.accessioned2020-03-05T11:46:23Z
dc.date.available2020-03-05T11:46:23Z
dc.date.issued2020-03
dc.description.abstractA major challenge in modelling and simulation is the need to combine expertise in both software technologies and a given scientific domain. When High-Performance Computing (HPC) is required to solve a scientific problem, software development becomes a problematic issue. Considering the complexity of the software for HPC, it is useful to identify programming languages that can be used to alleviate this issue. Because the existing literature on the topic of HPC is very dispersed, we performed a Systematic Mapping Study (SMS) in the context of the European COST Action cHiPSet. This literature study maps characteristics of various programming languages for data-intensive HPC applications, including category, typical user profiles, effectiveness, and type of articles. We organised the SMS in two phases. In the first phase, relevant articles are identified employing an automated keyword-based search in eight digital libraries. This lead to an initial sample of 420 papers, which was then narrowed down in a second phase by human inspection of article abstracts, titles and keywords to 152 relevant articles published in the period 2006-2018. The analysis of these articles enabled us to identify 26 programming languages referred to in 33 of relevant articles. We compared the outcome of the mapping study with results of our questionnaire-based survey that involved 57 HPC experts. The mapping study and the survey revealed that the desired features of programming languages for data-intensive HPC applications are portability, performance and usability. Furthermore, we observed that the majority of the programming languages used in the context of data-intensive HPC applications are text-based general-purpose programming languages. Typically these have a steep learning curve, which makes them difficult to adopt. We believe that the outcome of this study will inspire future research and development in programming languages for data-intensive HPC applications.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAMARAL, Vasco; [et al] – Programming languages for data-Intensive HPC applications: A systematic mapping study. Parallel Computing. ISSN 0167-8191. Vol. 91 (2020), pp. 1-17pt_PT
dc.identifier.doi10.1016/j.parco.2019.102584pt_PT
dc.identifier.issn0167-8191
dc.identifier.issn1872-7336
dc.identifier.urihttp://hdl.handle.net/10400.21/11200
dc.language.isoporpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relation10406 - European Cooperation in Science and Technology (COST)pt_PT
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dc.subjectHigh performance computing (HPC)pt_PT
dc.subjectBig datapt_PT
dc.subjectData-intensive applicationspt_PT
dc.subjectProgramming languagespt_PT
dc.subjectDomain-Specific language (DSL)pt_PT
dc.subjectGeneral-Purpose Language (GPL)pt_PT
dc.subjectSystematic mapping study (SMS)pt_PT
dc.titleProgramming languages for data-Intensive HPC applications: A systematic mapping studypt_PT
dc.typejournal article
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oaire.citation.endPage17pt_PT
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oaire.citation.titleParallel Computingpt_PT
oaire.citation.volume91pt_PT
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