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Visual MPI Performance Analysis using Event Flow Graphs
KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz).ORCID iD: 0000-0001-9693-6265
KTH, School of Computer Science and Communication (CSC), High Performance Computing and Visualization (HPCViz).ORCID iD: 0000-0002-9901-9857
2015 (English)In: Procedia Computer Science, ISSN 1877-0509, E-ISSN 1877-0509, Vol. 51, 1353-1362 p.Article in journal (Refereed) Published
Abstract [en]

Event flow graphs used in the context of performance monitoring combine the scalability and low overhead of profiling methods with lossless information recording of tracing tools. In other words, they capture statistics on the performance behavior of parallel applications while pre- serving the temporal ordering of events. Event flow graphs require significantly less storage than regular event traces and can still be used to recover the full ordered sequence of events performed by the application.  In this paper we explore the usage of event flow graphs in the context of visual performance analysis. We show that graphs can be used to quickly spot performance problems, helping to better understand the behavior of an application. We demonstrate our performance analysis approach with MiniFE, a mini-application that mimics the key performance aspects of finite- element applications in High Performance Computing (HPC).

Place, publisher, year, edition, pages
Elsevier, 2015. Vol. 51, 1353-1362 p.
Keyword [en]
visual performance analysis, event flow graphs, loop detection, MPI monitoring
National Category
Computer Systems
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-168701DOI: 10.1016/j.procs.2015.05.322OAI: oai:DiVA.org:kth-168701DiVA: diva2:817980
Conference
International Conference On Computational Science, ICCS 2015 Computational Science at the Gates of Nature
Note

QC 20150617

Available from: 2015-06-08 Created: 2015-06-08 Last updated: 2017-12-04Bibliographically approved

Open Access in DiVA

xaguilar_iccs2015(1782 kB)135 downloads
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Aguilar, XavierLaure, Erwin

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