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Understanding TAU: A Comprehensive Tutorial on Performance Measurement in Parallel Computing

This tutorial on the TAU Performance System provides an in-depth exploration of performance measurement, methodologies, and applications in complex parallel computing environments. Participants will learn about the system’s architecture, components such as instrumentation and analysis tools, and engage in practical demonstrations. The session aims to equip attendees with essential skills for performance problem solving and facilitate interactions for future collaborations. Join us to enhance your understanding of performance analysis with TAU for successful computation strategies.

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Understanding TAU: A Comprehensive Tutorial on Performance Measurement in Parallel Computing

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  1. TAU Parallel Performance SystemDOD UGC 2004 TutorialAllen D. Malony, Sameer Shende, Robert Bell{malony,sameer,bertie}@cs.uoregon.eduUnivesity of Oregon

  2. Tutorial Schedule 8:30 - 10:00 TAU overview and architecture 10:00 - 10:20 coffee break 10:20 - 11:50 TAU components and usage 11:50 - 1:10 lunch 1:10 - 2:40 TAU applications and developments 2:40 - 3:00 break 3:00 - 4:30 TAU demonstrations 4:30 - 5:00 Q&A

  3. Tutorial Outline – Part 1 TAU Overview and Architecture (1.5 hours) • Introduction • Performance technology • Complexity challenges and general problems • Computation Model for Performance Technology • Framework for performance problem solving • Performance analysis methods • TAU Performance System • Model-oriented framework architecture • TAU performance system toolkit • TAU features, status, and application

  4. Tutorial Outline – Part 2 TAU Components and Usage (1.5 hours) • Configuration • Instrumentation • Source, library, dynamic, multi-level • Measurement • Profiling and tracing • Analysis • ParaProf • Vampir • Examples of use

  5. Tutorial Outline – Parts 3 and 4 TAU Applications and Developments (1.5 hours) TAU Demonstrations (1+ hours)

  6. Tutorial Goals • Learn about the TAU performance system: measurement API, configuration, and analysis tools • Understand how TAU is applied in complex parallel computation scenarios • Develop an appreciation for performance problem solving in complex computational environments • Consider how TAU may be applied to performance problems of tutorial participants • Meet tutorial participants and provide opportunity for follow-on interaction

  7. Biographical Sketch - Allen D. Malony • Education • B.S., 1980 University of California, Los Angeles • M.S., 1982 University of California, Los Angeles • Ph.D., 1991 University of Illinois, Urbana-Champaign • Professional • Senior software engineer, Center for Supercomputing Research and Development (CSRD), UIUC • Assistant / Associate / Full Professor (1991, 1996, 2003), Computer Science, University of Oregon • Awards • Fulbright Research Scholar (The Netherlands, Austria)NSF Young Investigator, von Humboldt Senior Scholar

  8. Slides • ftp://ftp.cs.uoregon.edu/pub/malony/UGC2004 • intro-final.pdf • overview-final.pdf • component-final.pdf • application-final.pdf

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