Extending Scalasca’s Analysis Features

Daniel Lorenz (), David Böhme, Bernd Mohr, Alexandre Strube and Zoltán Szebenyi
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Daniel Lorenz: Forschungszentrum Jülich GmbH, Jülich Supercomputing Centre
David Böhme: German Research School of Simulation Science GmbH
Bernd Mohr: Forschungszentrum Jülich GmbH, Jülich Supercomputing Centre
Alexandre Strube: Forschungszentrum Jülich GmbH, Jülich Supercomputing Centre
Zoltán Szebenyi: German Research School of Simulation Science GmbH

A chapter in Tools for High Performance Computing 2012, 2013, pp 115-126 from Springer

Abstract: Abstract Scalasca is a performance analysis tool, which parses the trace of an application run for certain patterns that indicate performance inefficiencies. In this paper, we present recently developed new features in Scalasaca. In particular, we describe two newly implemented analysis methods: the root cause analysis which tries to identify the cause of a delay and the critical path analysis, which analyses the path of execution that determines the application runtime. Furthermore, we present time-series profiling, a method that allows to explore time-dependent behavior of an application. Finally, we extended the means of Scalasca and its output format CUBE to define and display topologies.

Keywords: Critical Path; Load Imbalance; Delay Cost; Virtual Topology; Delay Analysis (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-37349-7_8

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DOI: 10.1007/978-3-642-37349-7_8

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