Change search
ReferencesLink to record
Permanent link

Direct link
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, 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
URN: urn:nbn:se:kth:diva-168701DOI: 10.1016/j.procs.2015.05.322OAI: diva2:817980
International Conference On Computational Science, ICCS 2015 Computational Science at the Gates of Nature

QC 20150617

Available from: 2015-06-08 Created: 2015-06-08 Last updated: 2015-06-17Bibliographically approved

Open Access in DiVA

xaguilar_iccs2015(1782 kB)73 downloads
File information
File name FULLTEXT01.pdfFile size 1782 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Other links

Publisher's full textSciencedirect

Search in DiVA

By author/editor
Aguilar, XavierLaure, Erwin
By organisation
High Performance Computing and Visualization (HPCViz)
In the same journal
Procedia Computer Science
Computer Systems

Search outside of DiVA

GoogleGoogle Scholar
Total: 73 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 232 hits
ReferencesLink to record
Permanent link

Direct link