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Programming Abstractions for Data Locality

hal.structure.identifierCray, Inc.
dc.contributor.authorTATE, Adrian
hal.structure.identifierLawrence Berkeley National Laboratory [Berkeley] [LBNL]
dc.contributor.authorKAMIL, Amir
hal.structure.identifierLawrence Berkeley National Laboratory [Berkeley] [LBNL]
dc.contributor.authorDUBEY, Anshu
hal.structure.identifierUniversity of Passau
dc.contributor.authorGRÖSSLINGER, Armin
hal.structure.identifierCray, Inc.
dc.contributor.authorCHAMBERLAIN, Brad
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierEfficient runtime systems for parallel architectures [RUNTIME]
dc.contributor.authorGOGLIN, Brice
hal.structure.identifierSandia National Laboratories [Livermore]
dc.contributor.authorEDWARDS, Carter
hal.structure.identifierINTEL
dc.contributor.authorNEWBURN, Chris J.
hal.structure.identifierDepartment of Computer Science [UIUC] [UIUC]
dc.contributor.authorPADUA, David
hal.structure.identifierLawrence Berkeley National Laboratory [Berkeley] [LBNL]
dc.contributor.authorUNAT, Didem
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierEfficient runtime systems for parallel architectures [RUNTIME]
dc.contributor.authorJEANNOT, Emmanuel
hal.structure.identifierFriedrich-Alexander Universität Erlangen-Nürnberg = University of Erlangen-Nuremberg [FAU]
dc.contributor.authorHANNIG, Frank
hal.structure.identifierDepartment of Computer Science [ETH Zürich] [D-INFK]
dc.contributor.authorGYSI, Tobias
hal.structure.identifierKing Abdullah University of Science and Technology [Saudi Arabia] [KAUST]
dc.contributor.authorLTAIEF, Hatem
hal.structure.identifierIBM Almaden Research Center [San Jose]
dc.contributor.authorSEXTON, James
hal.structure.identifierBarcelona Supercomputing Center - Centro Nacional de Supercomputacion [BSC-CNS]
dc.contributor.authorLABARTA, Jesus
hal.structure.identifierLawrence Berkeley National Laboratory [Berkeley] [LBNL]
dc.contributor.authorSHALF, John
hal.structure.identifierLudwig Maximilian University [Munich] = Ludwig Maximilians Universität München [LMU]
dc.contributor.authorFÜRLINGER, Karl
hal.structure.identifierIBM Almaden Research Center [San Jose]
dc.contributor.authorO’BRIEN, Kathryn
hal.structure.identifierMax Planck Institute for Meteorology [MPI-M]
dc.contributor.authorLINARDAKIS, Leonidas
hal.structure.identifierDepartment of Computer Science [ETH Zürich] [D-INFK]
dc.contributor.authorBESTA, Maciej
hal.structure.identifierINTEL
dc.contributor.authorSAWLEY, Marie-Christine
hal.structure.identifierKTH Royal Institute of Technology [Stockholm] [KTH ]
dc.contributor.authorABRAHAM, Mark
hal.structure.identifierSwiss National Supercomputing Centre-SCR department [CSCS]
dc.contributor.authorBIANCO, Mauro
hal.structure.identifierChalmers University of Technology [Göteborg]
dc.contributor.authorPERICÀS, Miquel
hal.structure.identifierRIKEN - Institute of Physical and Chemical Research [Japon] [RIKEN]
dc.contributor.authorMARUYAMA, Naoya
hal.structure.identifierImperial College London
dc.contributor.authorKELLY, Paul H. J.
hal.structure.identifierNVIDIA [NVIDIA]
dc.contributor.authorMESSMER, Peter
hal.structure.identifierArgonne National Laboratory [Lemont] [ANL]
dc.contributor.authorROSS, Robert B.
hal.structure.identifierINTEL
dc.contributor.authorCLEDAT, Romain
hal.structure.identifierTokyo Institute of Technology [Tokyo] [TITECH]
dc.contributor.authorMATSUOKA, Satoshi
hal.structure.identifierSwiss National Supercomputing Centre-SCR department [CSCS]
dc.contributor.authorSCHULTHESS, Thomas
hal.structure.identifierDepartment of Computer Science [ETH Zürich] [D-INFK]
dc.contributor.authorHOEFLER, Torsten
hal.structure.identifierSandia National Laboratories [Livermore]
dc.contributor.authorLEUNG, Vitus J.
dc.date.accessioned2024-04-15T09:57:53Z
dc.date.available2024-04-15T09:57:53Z
dc.date.issued2014-11
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/198954
dc.description.abstractEnThe goal of the workshop and this report is to identify common themes and standardize concepts for locality-preserving abstractions for exascale programming models. Current software tools are built on the premise that computing is the most expensive component, we are rapidly moving to an era that computing is cheap and massively parallel while data movement dominates energy and performance costs. In order to respond to exascale systems (the next generation of high performance computing systems), the scientific computing community needs to refactor their applications to align with the emerging data-centric paradigm. Our applications must be evolved to express information about data locality. Unfortunately current programming environments offer few ways to do so. They ignore the incurred cost of communication and simply rely on the hardware cache coherency to virtualize data movement. With the increasing importance of task-level parallelism on future systems, task models have to support constructs that express data locality and affinity. At the system level, communication libraries implicitly assume all the processing elements are equidistant to each other. In order to take advantage of emerging technologies, application developers need a set of programming abstractions to describe data locality for the new computing ecosystem. The new programming paradigm should be more data centric and allow to describe how to decompose and how to layout data in the memory.Fortunately, there are many emerging concepts such as constructs for tiling, data layout, array views, task and thread affinity, and topology aware communication libraries for managing data locality. There is an opportunity to identify commonalities in strategy to enable us to combine the best of these concepts to develop a comprehensive approach to expressing and managing data locality on exascale programming systems. These programming model abstractions can expose crucial information about data locality to the compiler and runtime system to enable performance-portable code. The research question is to identify the right level of abstraction, which includes techniques that range from template libraries all the way to completely new languages to achieve this goal.
dc.language.isoen
dc.subject.endata layout
dc.subject.enabstractions
dc.subject.enaffinity
dc.subject.enlocality
dc.title.enProgramming Abstractions for Data Locality
dc.typeRapport
dc.subject.halInformatique [cs]/Architectures Matérielles [cs.AR]
dc.subject.halInformatique [cs]/Modélisation et simulation
dc.subject.halInformatique [cs]/Calcul parallèle, distribué et partagé [cs.DC]
dc.subject.halInformatique [cs]/Système d'exploitation [cs.OS]
bordeaux.page54
bordeaux.hal.laboratoriesLaboratoire Bordelais de Recherche en Informatique (LaBRI) - UMR 5800*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.type.institutionPADAL Workshop 2014, April 28--29, Swiss National Supercomputing Center (CSCS), Lugano, Switzerland
bordeaux.type.reportrr
hal.identifierhal-01083080
hal.version1
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01083080v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2014-11&rft.spage=54&rft.epage=54&rft.au=TATE,%20Adrian&KAMIL,%20Amir&DUBEY,%20Anshu&GR%C3%96SSLINGER,%20Armin&CHAMBERLAIN,%20Brad&rft.genre=unknown


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