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Measuring Computer Performance
A Practitioner's Guide

$56.00 ( ) USD

  • Date Published: January 2005
  • availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
  • format: Adobe eBook Reader
  • isbn: 9780511036279

$ 56.00 USD ( )
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About the Authors
  • Measuring Computer Performance sets out the fundamental techniques used in analyzing and understanding the performance of computer systems. The emphasis is on practical methods of measurement, simulation, and analytical modeling. David Lilja discusses performance metrics and provides detailed coverage of the strategies used in benchmark programs. In addition to intuitive explanations of key statistical tools, he describes the general "design of experiments" technique and shows how the maximum amount of information can be obtained with minimum effort. Features include appendices listing common probability distributions and statistical tables and a glossary of important technical terms.

    • Offers clear explanations of practical techniques for computer systems performance analysis
    • Provides intuitive coverage of key statistical tools
    • Integrates detailed descriptions of benchmark programmes
    • Includes a glossary of important technical terms
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    Reviews & endorsements

    "Lija's book is conceptually well formaulated, mathematically well grounded, and even intuitively appealing...This book is clearly an essential reference for professional engaed in computer (or network) performance measurement and capacity planning." Computing Reviews April 2001

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    Product details

    • Date Published: January 2005
    • format: Adobe eBook Reader
    • isbn: 9780511036279
    • contains: 38 b/w illus. 48 tables 104 exercises
    • availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
  • Table of Contents

    1. Introduction
    2. Metrics of performance
    3. Average performance and variability
    4. Errors in experimental measurements
    5. Comparing alternatives
    6. Measurement tools and techniques
    7. Benchmark programs
    8. Linear regression models
    9. Design of experiments
    10. Simulation and random number generation
    11. Queueing analysis
    Glossary
    Appendices.

  • Author

    David J. Lilja, University of Minnesota

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