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000173345 037__ $$aFZJ-2014-06755
000173345 041__ $$aEnglish
000173345 1001_ $$0P:(DE-Juel1)132112$$aGeimer, Markus$$b0$$eCorresponding Author$$ufzj
000173345 1112_ $$a26th International Conference for High Performance Computing, Networking, Storage and Analysis$$cNew Orleans, LA$$d2014-11-16 - 2014-11-21$$gSC'14$$wUSA
000173345 245__ $$aHands-On Practical Hybrid Parallel Application Performance Engineering$$f2014-11-16
000173345 260__ $$c2014
000173345 3367_ $$0PUB:(DE-HGF)31$$2PUB:(DE-HGF)$$aTalk (non-conference)$$btalk$$mtalk$$s1424427666_9319$$xAfter Call
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000173345 3367_ $$2DataCite$$aOther
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000173345 3367_ $$2BibTeX$$aINPROCEEDINGS
000173345 3367_ $$2ORCID$$aLECTURE_SPEECH
000173345 520__ $$aThis tutorial presents state-of-the-art performance tools for leading-edge HPC systems founded on the Score-P community-developed instrumentation and measurement infrastructure, demonstrating how they can be used for performance engineering of effective scientific applications based on standard MPI, OpenMP, hybrid combination of both, and increasingly common usage of accelerators. Parallel performance tools from the Virtual Institute - High Productivity Supercomputing (VI-HPS) are introduced and featured in hands-on exercises with Scalasca, Vampir, and TAU. We present the complete workflow of performance engineering, including instrumentation, measurement (profiling and tracing, timing and PAPI hardware counters), data storage, analysis, and visualization. Emphasis is placed on how tools are used in combination for identifying performance problems and investigating optimization alternatives. Using their own notebook computers with a provided Linux Live-ISO image containing all of the tools (running within a virtual machine or booted directly from DVD/USB) will help to prepare participants to locate and diagnose performance bottlenecks in their own parallel programs.
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000173345 536__ $$0G:(DE-Juel-1)ATMLPP$$aATMLPP - ATML Parallel Performance (ATMLPP)$$cATMLPP$$x1
000173345 7001_ $$0P:(DE-HGF)0$$aShende, Sameer S.$$b1
000173345 7001_ $$0P:(DE-HGF)0$$aWesarg, Bert$$b2
000173345 7001_ $$0P:(DE-Juel1)132302$$aWylie, Brian J. N.$$b3$$ufzj
000173345 7001_ $$0P:(DE-HGF)0$$aLinford, John$$b4
000173345 773__ $$y2014
000173345 8564_ $$uhttps://juser.fz-juelich.de/record/173345/files/FZJ-2014-06755.pdf$$yOpenAccess
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000173345 9141_ $$y2014
000173345 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)132112$$aForschungszentrum Jülich GmbH$$b0$$kFZJ
000173345 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)132302$$aForschungszentrum Jülich GmbH$$b3$$kFZJ
000173345 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
000173345 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
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