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000202902 0247_ $$2doi$$a10.1007/978-3-319-16012-2_1
000202902 037__ $$aFZJ-2015-05048
000202902 1001_ $$0P:(DE-Juel1)144419$$aZhukov, Ilya$$b0$$eCorresponding author
000202902 1112_ $$aTools for High Performance Computing 2014$$cStuttgart$$d2014-10-01 - 2014-10-02$$wGermany
000202902 245__ $$aScalasca v2: Back to the Future
000202902 260__ $$aCham$$bSpringer International Publishing$$c2015
000202902 29510 $$aNiethammer, Christoph (Editor) Chapter 1 ; ISBN: 978-3-319-16011-5 
000202902 300__ $$a1-24
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000202902 520__ $$aScalasca is a well-established open-source toolset that supports the performance optimization of parallel programs by measuring and analyzing their runtime behavior. The analysis identifies potential performance bottlenecks – in particular those concerning communication and synchronization – and offers guidance in exploring their causes. The latest Scalasca v2 release series is based on the community instrumentation and measurement infrastructure Score-P, which is jointly developed by a consortium of partners from Germany and the US. This significantly improves interoperability with other performance analysis tool suites such as Vampir and TAU due to the usage of the two common data formats CUBE4 for profiles and the Open Trace Format 2 (OTF2) for event trace data. This paper will showcase recent as well as ongoing enhancements, such as support for additional platforms (K computer, Intel Xeon Phi) and programming models (POSIX threads, MPI-3, OpenMP4), and features like the critical-path analysis. It also summarizes the steps necessary for users to migrate from Scalasca v1 to Scalasca v2.
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000202902 7001_ $$0P:(DE-Juel1)132244$$aFeld, Christian$$b1
000202902 7001_ $$0P:(DE-Juel1)132112$$aGeimer, Markus$$b2
000202902 7001_ $$0P:(DE-Juel1)132163$$aKnobloch, Michael$$b3
000202902 7001_ $$0P:(DE-Juel1)132199$$aMohr, Bernd$$b4
000202902 7001_ $$0P:(DE-Juel1)132249$$aSaviankou, Pavel$$b5
000202902 773__ $$a10.1007/978-3-319-16012-2_1
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