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Tools for application-oriented performance tuning
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Source International Conference on Supercomputing archive
Proceedings of the 15th international conference on Supercomputing table of contents
Sorrento, Italy
Pages: 154 - 165  
Year of Publication: 2001
ISBN:1-58113-410-X
Authors
John Mellor-Crummey  Dept. of Computer Science, Rice University, MS 132, 6100 Main Street, Houston, TX
Robert Fowler  Dept. of Computer Science, Rice University, MS 132, 6100 Main Street, Houston, TX
David Whalley  Dept. of Computer Science, Florida State University, Tallahassee, FL
Sponsor
SIGARCH: ACM Special Interest Group on Computer Architecture
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 2,   Downloads (12 Months): 37,   Citation Count: 14
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ABSTRACT

Application performance tuning is a complex process that requires assembling various types of information and correlating it with source code to pinpoint the causes of performance bottlenecks. Existing performance tools don't adequately support this process in one or more dimensions. We discuss some of the critical utility and usability issues for application-level performance analysis tools in the context of two performance tools, MHSim and HPCView, that we built to support our own work on data layout and optimizing compilers. MHsim is a memory hierarchy simulator that produces source-level information not otherwise available about memory hierarchy utilization and the causes of cache conflicts. HPCView is a tool that combines data from arbitrary sets of instrumentation sources and correlates it with program source code. Both tools report their results in scope-hierarchy views of the corresponding source code and produce their output as HTML databases that can be analyzed portably and collaboratively using a commodity browser. In addition to daily use within our group, the tools are being used successfully by several code development teams in DoD and DoE laboratories.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Carnival Web Site. http://www.cs.rochester.edu/u/leblanc/prediction.html.
 
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H. Davis, S. Goldschmidt, and J. Hennessy. Tango: A Multiprocessor Simulation and Tracing System. In Proceedings of the International Conference on Parallel Processing, pages 99-107, August 1991.
 
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A. J. Goldberg and J. Hennessy. MTOOL: A Method for Isolating Memory Bottlenecks in Shared Memory Multiprocessor Programs. In Proceedings of the International Conference on Parallel Processing, pages 251-257, August 1991.
 
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W3C Math Working Group. Mathematical markup language (mathml) 1.01 specification, July 1999. http://www.w3.org/TR/REC-MathML.
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C. Janssen. The Visual Profiler. http://aros.ca.sandia.gov/~cljanss/perf/vprof/doc/README.html.
 
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CITED BY  14

Collaborative Colleagues:
John Mellor-Crummey: colleagues
Robert Fowler: colleagues
David Whalley: colleagues