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000138577 0247_ $$2doi$$a10.1007/978-3-642-40698-0_13
000138577 037__ $$aFZJ-2013-04676
000138577 041__ $$aEnglish
000138577 1001_ $$0P:(DE-HGF)0$$aEichenberger, Alexandre E.$$b0$$eCorresponding author
000138577 1112_ $$a9th International Workshop on OpenMP$$cCanberra$$d2013-09-16 - 2013-09-18$$gIWOMP 2013$$wAustralia
000138577 245__ $$aOMPT: An OpenMP Tools Application Programming Interface for Performance Analysis
000138577 260__ $$aBerlin/Heidelberg$$bSpringer$$c2013
000138577 29510 $$aOpenMP in the Era of Low Power Devices and Accelerators
000138577 300__ $$a171 - 185
000138577 3367_ $$0PUB:(DE-HGF)8$$2PUB:(DE-HGF)$$aContribution to a conference proceedings$$bcontrib$$mcontrib$$s1384770918_17438
000138577 3367_ $$0PUB:(DE-HGF)7$$2PUB:(DE-HGF)$$aContribution to a book$$mcontb
000138577 3367_ $$033$$2EndNote$$aConference Paper
000138577 3367_ $$2ORCID$$aCONFERENCE_PAPER
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000138577 3367_ $$2BibTeX$$aINPROCEEDINGS
000138577 4900_ $$aLNCS$$v8122
000138577 520__ $$aA shortcoming of OpenMP standards to date is that they lack an application programming interface (API) to support construction of portable, efficient, and vendor-neutral performance tools. To address this issue, the tools working group of the OpenMP Language Committee has designed OMPT—a performance tools API for OpenMP. OMPT enables performance tools to gather useful performance information from applications with low overhead and to map this information back to a user-level view of applications. OMPT provides three principal capabilities: (1) runtime state tracking, which enables a sampling-based performance tool to understand what an application thread is doing, (2) callbacks and inquiry functions that enable sampling-based performance tools to attribute application performance to complete calling contexts, and (3) additional callback notifications that enable construction of more full-featured monitoring capabilities. The earnest hope of the tools working group is that OMPT be adopted as part of the OpenMP standard and supported by all standard-compliant OpenMP implementations.
000138577 536__ $$0G:(DE-HGF)POF2-411$$a411 - Computational Science and Mathematical Methods (POF2-411)$$cPOF2-411$$fPOF II$$x0
000138577 536__ $$0G:(DE-Juel-1)ATMLPP$$aATMLPP - ATML Parallel Performance (ATMLPP)$$cATMLPP$$x1
000138577 7001_ $$0P:(DE-HGF)0$$aMellor-Crummey, John$$b1
000138577 7001_ $$0P:(DE-HGF)0$$aSchulz, Martin$$b2
000138577 7001_ $$0P:(DE-HGF)0$$aWong, Michael$$b3
000138577 7001_ $$0P:(DE-HGF)0$$aCopty, Nawal$$b4
000138577 7001_ $$0P:(DE-HGF)0$$aDietrich, Robert$$b5
000138577 7001_ $$0P:(DE-HGF)0$$aLiu, Xu$$b6
000138577 7001_ $$0P:(DE-HGF)0$$aLoh, Eugene$$b7
000138577 7001_ $$0P:(DE-Juel1)138271$$aLorenz, Daniel$$b8$$ufzj
000138577 773__ $$a10.1007/978-3-642-40698-0_13
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000138577 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)138271$$aForschungszentrum Jülich GmbH$$b8$$kFZJ
000138577 9132_ $$0G:(DE-HGF)POF3-511$$1G:(DE-HGF)POF3-510$$2G:(DE-HGF)POF3-500$$aDE-HGF$$bKey Technologies$$lSupercomputing & Big Data $$vComputational Science and Mathematical Methods$$x0
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000138577 9141_ $$y2013
000138577 920__ $$lyes
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