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000893077 037__ $$aFZJ-2021-02545
000893077 1001_ $$0P:(DE-Juel1)132163$$aKnobloch, Michael$$b0$$eCorresponding author
000893077 1112_ $$aTools for High Performance Computing 2019$$cDresden$$d2019-09-02 - 2019-09-03$$wFed Rep Germany
000893077 245__ $$aA Picture Is Worth a Thousand Numbers—Enhancing Cube’s Analysis Capabilities with Plugins
000893077 260__ $$aCham$$bSpringer International Publishing$$c2021
000893077 29510 $$aTools for High Performance Computing 2018 / 2019 / Mix, Hartmut (Editor) ; Cham : Springer International Publishing, 2021, Chapter 13 ; ISBN: 978-3-030-66056-7 ; doi:10.1007/978-3-030-66057-4
000893077 300__ $$a237 - 259
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000893077 520__ $$aIn the last couple of years, supercomputers became increasingly large and more and more complex. Performance analysis tools need to adapt to the system complexity in order to be used effectively at large scale. Thus, we introduced a plugin infrastructure in Cube 4, the performance report explorer for Score-P and Scalasca, which allows to extend Cube’s analysis features without modifying the source code of the GUI. In this paper we describe the Cube plugin infrastructure and show how it makes Cube a more versatile and powerful tool. We present different plugins provided by JSC that extend and enhance the CubeGUI’s analysis capabilities. These add new types of system-tree visualizations, help create reasonable filter files for Score-P and visualize simple OTF2 trace files. We also present a plugin which provides a high-level overview of the efficiency of the application and its kernels. We further discuss context-free plugins, which are used to integrate command-line Cube algebra utilities, like cube_diff and similar commands, in the GUI.
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000893077 536__ $$0G:(DE-Juel-1)ATMLPP$$aATMLPP - ATML Parallel Performance (ATMLPP)$$cATMLPP$$x1
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000893077 7001_ $$0P:(DE-Juel1)132249$$aSaviankou, Pavel$$b1$$ufzj
000893077 7001_ $$0P:(DE-Juel1)142180$$aSchlütter, Marc$$b2$$ufzj
000893077 7001_ $$0P:(DE-Juel1)132282$$aVisser, Anke$$b3$$ufzj
000893077 7001_ $$0P:(DE-Juel1)132199$$aMohr, Bernd$$b4$$ufzj
000893077 773__ $$a10.1007/978-3-030-66057-4_13
000893077 8564_ $$uhttps://juser.fz-juelich.de/record/893077/files/paper.pdf$$yOpenAccess
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000893077 9130_ $$0G:(DE-HGF)POF3-511$$1G:(DE-HGF)POF3-510$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lSupercomputing & Big Data$$vComputational Science and Mathematical Methods$$x0
000893077 9141_ $$y2021
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