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VPPB: A Visualization and Performance Prediction Tool for Multitreaded Solaris Programs
Responsible organisation
1998 (English)Conference paper, Published paper (Refereed) Published
Abstract [en]

Efficient performance tuning of parallel programs is often hard. In this paper we describe an approach that uses a uni-processor execution of a multithreaded program as reference to simulate a multiprocessor execution. The speed-up is predicted, and the program behaviour is visualized as a graph, which can be used in the performance tuning process. The simulator considers scheduling as well as hardware parameters, e.g., the thread priority, no. of LWPs, and no. of CPUs. The visualization part shows the simulated execution in two graphs: one showing the threads’ behaviour over time and the other the amount of parallel-ism over time. In the first graph is it possible to relate an event in the graph to the code line causing the event. Validation using a Sun multiprocessor with eight processors and five scientific parallel applications shows that the speed-up predictions are within +/-6% of a real execution.

Place, publisher, year, edition, pages
Orlando, FL, USA: IEEE Computer Soc. , 1998.
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:bth-10101Local ID: oai:bth.se:forskinfo423C2F8686C2876FC12568A3002CAB52ISBN: 0818684046 (print)OAI: oai:DiVA.org:bth-10101DiVA, id: diva2:838134
Conference
12th International Parallel Processing Symposium
Available from: 2012-09-18 Created: 2000-03-15 Last updated: 2018-02-02Bibliographically approved

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fulltext(140 kB)373 downloads
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File name FULLTEXT01.pdfFile size 140 kBChecksum SHA-512
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Type fulltextMimetype application/pdf

Authority records

Lundberg, LarsGrahn, Håkan

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf