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Neil J. Gunther
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The Practical Performance Analyst: Performance-By-Design Techniques for Distributed Systems (McGraw-Hill Series on Computer Communications) Har/Dsk Edition

by Neil J. Gunther (Author)
4.9 4.9 out of 5 stars 8 ratings
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The complex mathematical formulas upon which performace analysis is based have made it inaccessible to many. Here is the first book to explain both theory and practical applications in an intuitive way for computer professionals, especially those working large distributed systems. It shows how to apply performance analysis to all kinds of large-scale computer systems, including client/server, data communications, and telecommunications systems, to achieve high performance. The accompanying disk includes a queuing analysis tool.
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  1. ISBN-10
    0079129463
  2. ISBN-13
    978-0079129468
  3. Edition
    Har/Dsk
  4. Publisher
    McGraw-Hill
  5. Publication date
    January 1, 1998
  6. Language
    English
  7. Dimensions
    7.75 x 1.5 x 9.75 inches
  8. Print length
    432 pages
  9. See all details
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Editorial Reviews

From the Back Cover

At last! Performance analysis made easy and applicable for large distributed systems. Here is a practical new perspective on performance analysis--one that makes this difficult subject understandable and useful. It demystifies the complex underlying formulas, and shows how to apply performance analysis to all kinds of large-scale computer systems, including client/server and communications systems. At the heart of this book is a unique methodology called performance-by-design. Timeless and independent of any specific technology, it is a tested approach for ensuring that goals are set and met. The emphasis is on assessing overall performance in large-scale systems, not just tuning one particular hardware subsystem or software compoenet. The chief tool supporting this methodology is the queueing analyzer, the C source code of which is provided on the accompanying diskette. This tool enables you to bypass such arcane concerns as the mathematics of queueing theory, and cut right to the real-world chase. Written in a friendly, intuitive style, this book will help you master performance analysis and apply it at either end of the development cycle: to support decisions in the early stages of system design, or to evaluate your existing system. ABOUT THE AUTHOR: Neil J. Gunther was born in Melbourne, Australia. He holds a Ph.D. in theoretical physics from the University of Southampton, England, and began working in American's Silicon Valley at the dawn of the PC revolution. After eight years as a researcher at the Xerox Palo Alto Research Center, he joint Pyramid Technology as a Senior Scientist and Manager of Performance Analysis. In 1994 he founded Computer Dynamics Consulting, advising such clients as Amdahl Corporation, Tandem Computers, and Demand Technology on performance tool development and planning strategies for large-scale computer systems. Dr. Gunther is also a developer of distributed performance management tools, worldwide lecturer, and author of more than 50 professional articles. He lives in Mountain View, California.

About the Author

Neil J. Gunther was born in Melbourne, Australia. He holds a Ph.D. in theoretical physics from the University of Southampton, England, and began working in America's Silicon Valley at the dawn of the PC revolution. After eight years as a researcher at the Xerox Palo Alto Research Center, he joined Pyramid Technology as a Senior Scientist and Manager of Performance Analysis. In 1994 he founded Computer Dynamics Consulting, advising such clients as Amdahl Corporation, Tandem Computers, and Demand Technology on performance tool development and planning strategies for large-scale computer systems. Dr. Gunther is also a developer of distributed performance management tools, worldwide lecturer, and author of more than 50 professional articles. He lives in Mountain View, California.

Product details

  • Publisher ‏ : ‎ McGraw-Hill; Har/Dsk edition (January 1, 1998)
  • Language ‏ : ‎ English
  • Hardcover ‏ : ‎ 432 pages
  • ISBN-10 ‏ : ‎ 0079129463
  • ISBN-13 ‏ : ‎ 978-0079129468
  • Item Weight ‏ : ‎ 2.51 pounds
  • Dimensions ‏ : ‎ 7.75 x 1.5 x 9.75 inches
  • Customer Reviews:
    4.9 4.9 out of 5 stars 8 ratings

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Customer reviews

4.9 out of 5 stars
8 global ratings

Top reviews from the United States

Mike Tarrani
5.0 out of 5 stars Solid, readable and covers topics not found elsewhere
Reviewed in the United States on April 21, 2002
Verified Purchase
Although this book's full value will be realized if you understand the C programming language (he uses source code it illustrate points throughout the book and provides a C library for performance analysis on the accompanying disk), anyone with good math skills will gain much from this outstanding book.
The core approach is Performance By Design, which is aligned to product development. His approach, if used properly, will ensure that performance goals are established in the design phase, and are met as a system or software evolves through the development life cycle.
Highlights of the book are:
(1) Through introduction to the foundation of performance: queuing, parallelism and multiprocessor systems.
(2) Coverage of contemporary issues, such as client/server and web system performance,
(3) Unexpected forays into performance characteristics and considerations that I've encountered in no other book. For example, Part 3 of this book addresses subtle issues such as transient analysis, scaling behavior and similar topics. Here the author integrates theoretical physics into performance analysis - while this may seem odd, it only reinforces that much can be added to the performance analysis body of knowledge by drawing from sources outside of computer science. His qualifications for this material includes a Ph.D in theoretical physics, and his ability to clearly explain concepts that are foreign to the average computer scientist or performance practitioner is excellent.
I like the conversation style that the author employs, the way he starts with the basics and builds upon them and the thoroughness in which all aspects of performance are discussed. More importantly, although advanced math concepts are introduced the way they are presented can be understood by anyone with high school or college freshman knowledge of probability and calculus.
18 people found this helpful
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TheScott
5.0 out of 5 stars New member of my capacity planning arsenal
Reviewed in the United States on August 16, 2008
Excellent insight into the capacity planning process and how it relates to distributed computing. This book works best when coupled with the "Guerrilla Capacity Planning" and "Analyzing Computer System Performance with Perl::PDQ" books by Dr. Gunther. He explores queuing theory in-depth and explains how you relate this to real-world capacity planning.

His writing style is easy to understand - not only does he give you the theoretical background, he shows the practical application and the results. He also includes code examples for the "PDQ" analyzer which is a software program he wrote which leverages his "Universal Law of Scalability." For more information, check out his web site at [...]

I highly recommend this book if you are a capacity or performance analyst and are interested in real-world application rather than just another boring queuing theory textbook.
One person found this helpful
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Fishman
5.0 out of 5 stars A must have book with free software too!
Reviewed in the United States on September 17, 2006
The author provides good practical coverage of queuing concepts and then goes on to show how to use queuing models.

I found it interesting that he gives an example of typical computer time periods scaled up to human proportions. If a computer clock speed in nanoseconds were analagous to seconds then a main memory access of 100 cpu cycles would be like some minutes and a disk access would be like some months.

His coverage of queuing concepts is very accessible with a minimum of math.

Scalability is frequently discussed concept that often is not very well quantified. He has the most original approach to quantifying scalability that I have seen.

A queuing modeling package called PDQ is also provided with the book. The source code in C is provided for the PDQ package.

There are some PDQ examples within the book. This is a real bargain because certainly the PDQ software is worth much more than the cost of the book.

If you have and interest in capacity planning and performance analysis (especially if you work in this area) this is a must have book.
4 people found this helpful
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Photo/Video Gearhead
4.0 out of 5 stars A useful introduction to scalability, but not a universal approach
Reviewed in the United States on December 18, 2012
In this book and its two predecessors, "Guerrilla Capacity Planning" and "Analyzing Computer System Performance with Perl::PDQ", Dr. Neil Gunther provides a useful introduction to the topic of measuring and modeling the scalability of parallel computer systems. The model that he advocates in his books is a useful starting point; however, this model fails to provide a sufficiently general basis for modeling the behavior of the wide variety of current parallel computer systems.

The "universal scalability law" that he discusses extends Amdahl's Law via the addition of a "queuing" term that models effects such as data exchange between parallel processes. And although Dr. Gunther suggests that this queuing term ought to grow linearly with the number of parallel processes, this queuing term depends on the specific communication architecture of the computer system and can grow non-linearly, for example, as log to the base two of the number of processes.

This logarithmic growth law can occur because one processor may not communicate directly with all other processors. Instead, one processor may send information to two other processors, and each of those two processors may send information to two more processors, and so forth. Therefore, in order to model the communication that occurs in such a communication cascade, the queuing term should grow as log(n).

Moreover, performance data that are obtained from current parallel computer systems do not always conform to Dr. Gunther's "universal" scalability "law" under other conditions. For example, a large volume of data that exceeds the capacity of the total cache memory when distributed across a few processors may well fit into total cache memory when distributed across a larger number of processors. Under these conditions, the scalability for the larger number of processors appears to grow "super-linearly" relative to the scalability of a few processors. Thus, although Dr. Gunther's book is a useful introduction to the subject of measuring and modeling the behavior of parallel computer architectures, his universal scalability law should not be considered to be universal.
2 people found this helpful
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Top reviews from other countries

Amazon Customer
5.0 out of 5 stars Learn the art of performance modeling
Reviewed in India on March 20, 2019
Verified Purchase
This is a must have book for everyone in programming.
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