000152042 001__ 152042
000152042 005__ 20250314084110.0
000152042 0247_ $$2doi$$a10.3233/978-1-61499-381-0-783
000152042 0247_ $$2WOS$$aWOS:000452120400079
000152042 020__ $$a978-1-61499-380-3
000152042 037__ $$aFZJ-2014-01862
000152042 1001_ $$0P:(DE-HGF)0$$aJaeger, Julien$$b0$$eCorresponding Author
000152042 1112_ $$aInternational Conference on Parallel Computing$$cMunich$$d2013-09-10 - 2013-09-13$$gParCo 2013$$wGermany
000152042 245__ $$aBinary Instrumentation for Scalable Performance Measurement of OpenMP Applications
000152042 260__ $$bIOS Press$$c2014
000152042 29510 $$aParallel Computing: Accelerating Computational Science and Engineering (CSE)
000152042 300__ $$a783 - 792
000152042 3367_ $$0PUB:(DE-HGF)8$$2PUB:(DE-HGF)$$aContribution to a conference proceedings$$bcontrib$$mcontrib$$s1396418051_15498
000152042 3367_ $$0PUB:(DE-HGF)7$$2PUB:(DE-HGF)$$aContribution to a book$$mcontb
000152042 3367_ $$033$$2EndNote$$aConference Paper
000152042 3367_ $$2ORCID$$aCONFERENCE_PAPER
000152042 3367_ $$2DataCite$$aOutput Types/Conference Paper
000152042 3367_ $$2DRIVER$$aconferenceObject
000152042 3367_ $$2BibTeX$$aINPROCEEDINGS
000152042 4900_ $$aAdvances in Parallel Computing$$v25
000152042 520__ $$aIn this paper we present a binary instrumentation methodology to monitor runtime events. We demonstrate our approach on OpenMP constructs for the Intel and GNU compilers. A binary-level static analysis detects the compiler patterns and the runtime function calls corresponding to OpenMP regions. To this effect we integrate the software tool MAQAO with the scalable measurement infrastructure Score-P. We design a new interface and modify both tools to support the new events. The main advantages of using binary instrumentation are the possibility to retrieve implicit runtime events, to instrument without recompilation, to be independent from the language, and not to interact with compiler optimization. Our validation experiments and first results shows that binary instrumentation has not introduced any additional overhead.
000152042 536__ $$0G:(DE-HGF)POF2-411$$a411 - Computational Science and Mathematical Methods (POF2-411)$$cPOF2-411$$fPOF II$$x0
000152042 536__ $$0G:(DE-Juel-1)ATMLPP$$aATMLPP - ATML Parallel Performance (ATMLPP)$$cATMLPP$$x1
000152042 7001_ $$0P:(DE-Juel1)143710$$aPhilippen, Peter$$b1$$ufzj
000152042 7001_ $$0P:(DE-HGF)0$$aPetit, Eric$$b2
000152042 7001_ $$0P:(DE-HGF)0$$aRubial, Andres Charif$$b3
000152042 7001_ $$0P:(DE-Juel1)132244$$aRössel, Christian$$b4$$ufzj
000152042 7001_ $$0P:(DE-HGF)0$$aJalby, William$$b5
000152042 7001_ $$0P:(DE-Juel1)132199$$aMohr, Bernd$$b6$$ufzj
000152042 773__ $$a10.3233/978-1-61499-381-0-783
000152042 909CO $$ooai:juser.fz-juelich.de:152042$$pVDB
000152042 9141_ $$y2014
000152042 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)143710$$aForschungszentrum Jülich GmbH$$b1$$kFZJ
000152042 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)132244$$aForschungszentrum Jülich GmbH$$b4$$kFZJ
000152042 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)132199$$aForschungszentrum Jülich GmbH$$b6$$kFZJ
000152042 9132_ $$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$$x0
000152042 9131_ $$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$$x0
000152042 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
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