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000153477 0247_ $$2doi$$a10.1007/978-3-642-54420-0_61
000153477 0247_ $$2ISSN$$a1611-3349
000153477 0247_ $$2ISSN$$a0302-9743
000153477 037__ $$aFZJ-2014-03075
000153477 082__ $$a004
000153477 1001_ $$0P:(DE-Juel1)144419$$aZhukov, Ilya$$b0$$eCorresponding Author$$ufzj
000153477 1112_ $$aEuro-Par 2013: Parallel Processing Workshops$$cAachen$$d2013-08-26 - 2013-08-27$$wGermany
000153477 245__ $$aAssessing Measurement and Analysis Performance and Scalability of Scalasca 2.0
000153477 260__ $$aBerlin, Heidelberg$$bSpringer Berlin Heidelberg$$c2014
000153477 29510 $$aEuro-Par 2013: Parallel Processing Workshops
000153477 300__ $$a627 - 636
000153477 3367_ $$0PUB:(DE-HGF)8$$2PUB:(DE-HGF)$$aContribution to a conference proceedings$$bcontrib$$mcontrib$$s1399880741_4092
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000153477 3367_ $$2BibTeX$$aINPROCEEDINGS
000153477 4900_ $$aLecture Notes in Computer Science$$v8374
000153477 520__ $$aThe Scalasca toolset was developed to provide highly scalable performance measurement and analysis of scientific applications on current HPC platforms, including leadership systems such as IBM BlueGene/Q and more traditional Linux clusters. Its primary focus is support for C/C++/Fortran applications using MPI and OpenMP, and mixed-mode combinations thereof, offering detailed call-path profiles for each process and thread produced by runtime summarization or augmented with wait-state analysis of event traces. A new generation of Scalasca (2.0) uses the community-developed infrastructure comprising of Score-P and associated components, while continuing to provide the previous functionality. By comparing the new version of Scalasca with its predecessor, using the applications from the NPB3.3-MZ-MPI benchmark suite, we validate core functionality and assess overheads and scalability. Although adequate for general use, various aspects are identified for further improvement, particularly for larger scales.
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000153477 7001_ $$0P:(DE-Juel1)132302$$aWylie, Brian J. N.$$b1$$ufzj
000153477 773__ $$a10.1007/978-3-642-54420-0_61
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000153477 9141_ $$y2014
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