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000128133 005__ 20210129211113.0
000128133 037__ $$aFZJ-2012-01028
000128133 1001_ $$0P:(DE-HGF)0$$aHammond, Jeff R.$$b0$$eCorresponding author
000128133 1112_ $$aThe 6th Conference on Partitioned Global Address Space Programming Models$$cSanta Barbara, California$$d2012-10-10 - 2012-10-12$$gPGAS 12$$wUSA
000128133 245__ $$aOSPRI: An Optimized One-Sided Communication Runtime for Leadership-Class Machines
000128133 260__ $$c2012
000128133 300__ $$a10 p.
000128133 3367_ $$0PUB:(DE-HGF)8$$2PUB:(DE-HGF)$$aContribution to a conference proceedings$$bcontrib$$mcontrib$$s1392987033_17915
000128133 3367_ $$033$$2EndNote$$aConference Paper
000128133 3367_ $$2ORCID$$aCONFERENCE_PAPER
000128133 3367_ $$2DataCite$$aOutput Types/Conference Paper
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000128133 3367_ $$2BibTeX$$aINPROCEEDINGS
000128133 500__ $$3POF3_Assignment on 2016-02-29
000128133 520__ $$aAbstract—Partitioned Global Address Space (PGAS) programming models provide a convenient approach to implementing complex scienti?c applications by providing access to a large, globally accessible address space. This paper describes the design, implementation and performance of a new one-sided communication library that attempts to meet the needs of PGAS models, particularly Global Arrays, but hopefully also PGAS languages like UPC and CAF. In this work, we describe a new communication runtime for PGAS models such as GA, termed OSPRI (One-Sided PRImitives). OSPRI presents several changes in architecture from conventional one-sided communication systems that make it better suited for emerging leadersip class machines. We describe the implementation of the the IBM Blue Gene/P target for OSPRI and demonstrate signi?cant improvements in latency, bandwidth, and scalability over tuned ARMCI and GA implementations on this system. The performance and scalablity of this library validate the design choices and should provide useful insight for implementers of related communication middleware.
000128133 536__ $$0G:(DE-HGF)POF2-411$$a411 - Computational Science and Mathematical Methods (POF2-411)$$cPOF2-411$$fPOF II$$x0
000128133 536__ $$0G:(DE-Juel1)FMM-20140729$$aFMM - Fast Multipole Method (FMM-20140729)$$cFMM-20140729$$x1
000128133 7001_ $$0P:(DE-HGF)0$$aDinan, James$$b1
000128133 7001_ $$0P:(DE-HGF)0$$aBalaji, Pavan$$b2
000128133 7001_ $$0P:(DE-Juel1)132152$$aKabadshow, Ivo$$b3
000128133 7001_ $$0P:(DE-HGF)0$$aPotluri, Sreeram$$b4
000128133 7001_ $$0P:(DE-HGF)0$$aTipparaju, Vinod$$b5
000128133 8564_ $$uhttp://www.mcs.anl.gov/~balaji/pubs/2012/pgas/pgas12.ospri.pdf
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000128133 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)132152$$aForschungszentrum Jülich GmbH$$b3$$kFZJ
000128133 9132_ $$0G:(DE-HGF)POF3-519H$$1G:(DE-HGF)POF3-510$$2G:(DE-HGF)POF3-500$$aDE-HGF$$bKey Technologies$$lSupercomputing & Big Data $$vAddenda$$x0
000128133 9131_ $$0G:(DE-HGF)POF2-411$$1G:(DE-HGF)POF2-410$$2G:(DE-HGF)POF2-400$$3G:(DE-HGF)POF2$$4G:(DE-HGF)POF$$aDE-HGF$$bSchlüsseltechnologien$$lSupercomputing$$vComputational Science and Mathematical Methods$$x0
000128133 9141_ $$y2012
000128133 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
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