Managing Performance Analysis with Dynamic Statistical Projection Pursuit

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Computer systems and applications are growing more complex. Consequently, performance analysis has become more difficult due to the complex, transient interrelationships among runtime components. To diagnose these types of performance issues, developers must use detailed instrumentation to capture a large number of performance metrics. Unfortunately, this instrumentation may actually influence the performance analysis, leading the developer to an ambiguous conclusion. In this paper, we introduce a technique for focusing a performance analysis on interesting performance metrics. This technique, called dynamic statistical projection pursuit, identifies interesting performance metrics that the monitoring system should capture across some number of processors. By reducing ... continued below

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383 Kilobytes pages

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Vetter, J.S. & Reed, D.A. May 22, 2000.

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Computer systems and applications are growing more complex. Consequently, performance analysis has become more difficult due to the complex, transient interrelationships among runtime components. To diagnose these types of performance issues, developers must use detailed instrumentation to capture a large number of performance metrics. Unfortunately, this instrumentation may actually influence the performance analysis, leading the developer to an ambiguous conclusion. In this paper, we introduce a technique for focusing a performance analysis on interesting performance metrics. This technique, called dynamic statistical projection pursuit, identifies interesting performance metrics that the monitoring system should capture across some number of processors. By reducing the number of performance metrics, projection pursuit can limit the impact of instrumentation on the performance of the target system and can reduce the volume of performance data.

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383 Kilobytes pages

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  • High Performance Network and Computing Conference, Portland, OR (US), 11/13/1999

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  • Report No.: UCRL-JC-136327
  • Grant Number: W-7405-Eng-48
  • Office of Scientific & Technical Information Report Number: 791439
  • Archival Resource Key: ark:/67531/metadc733791

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Office of Scientific & Technical Information Technical Reports

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  • May 22, 2000

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  • Oct. 19, 2015, 7:39 p.m.

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  • May 6, 2016, 4 p.m.

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Vetter, J.S. & Reed, D.A. Managing Performance Analysis with Dynamic Statistical Projection Pursuit, article, May 22, 2000; California. (digital.library.unt.edu/ark:/67531/metadc733791/: accessed January 17, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.