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The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling 1st Edition

4.5 out of 5 stars 21 customer reviews
ISBN-13: 978-0471503361
ISBN-10: 0471503363
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Editorial Reviews

Review

"At last, a welcome and needed text for computer professionals who require practical, ready-to-apply techniques for performance analysis. Highly recommended!" -Dr. Leonard Kleinrock University of California, Los Angeles "An entirely refreshing text which has just the right mixture of theory and real world practice. The book is ideal for both classroom instruction and self-study." -Dr. Raymond L. Pickholtz President, IEEE Communications Society "An extraordinarily comprehensive treatment of both theoretical and practical issues." -Dr. Jeffrey P. Buzen Internationally recognized performance analysis expert ". it is the most thorough book available to date" -Dr. Erol Gelenbe Universite Rene Descartes, Paris ". an extraordinary book. A worthy addition to the bookshelf of any practicing computer or communications engineer" -Dr. Vinton G. Cerf Chairman, ACM SIGCOMM "This is an unusual object, a textbook that one wants to sit down and peruse. The prose is clear and fluent, but more important, it is witty." -Allison Mankin The Mitre Washington Networking Center Newsletter

From the Inside Flap

As a key step in the selection of processors, operating systems, database, systems networks, and languages, performance analysis plays an integral role in the design and procurement of new computer systems. Presenting a unique blend of measurement, simulation, and modeling methods in a straightforward, problem-oriented fashion, The Art of Computer Systems Performance Analysis is a computer professional's treasure trove for practical performance analysis techniques. Integrating essential queueing theory with simulation, measurement techniques, data analysis, and experimental design, the book is divided into the following comprehensive parts:
* Overview of Performance Evaluation-addresses common mistakes in the evaluation process, criteria for selecting evaluation techniques and performance metrics, and the establishment of performance requirements
* Measurement Techniques and Tools-examines workload selection and characterization, monitors, capacity planning and benchmarking, data presentation, and ratio games
* Probability and Statistics-discusses the summarization of measured data, the comparison of systems using sample data, and regression models
* Experimental Design and Analysis-provides the maximum amount of information with the minimum number of experiments
* Simulation-clarifies the analysis of results, model verification, validation, and random-number generation
* Queueing Models-models and techniques for the solution of a wide variety of common performance problems
Analysis techniques are supported by more than 150 examples and case studies-all from the computer science field-and many are summarized with results in handy reference boxes. In addition, common mistakes in the application of various techniques are descussed, and a host of special tricks to demonstrate system superiority are revealed. The Art of Computer Systems Performance Analysis is an essential tool for performance analysts, designers, purchasers, and users of computer systems.
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Product Details

  • Hardcover: 685 pages
  • Publisher: Wiley; 1 edition (April 1991)
  • Language: English
  • ISBN-10: 0471503363
  • ISBN-13: 978-0471503361
  • Product Dimensions: 6.3 x 1.5 x 9.6 inches
  • Shipping Weight: 2.5 pounds (View shipping rates and policies)
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (21 customer reviews)
  • Amazon Best Sellers Rank: #250,605 in Books (See Top 100 in Books)

More About the Author

Raj Jain is a Fellow of IEEE, a Fellow of ACM, a Fellow of AAAS, a winner of 2015 A.A. Michelson Award, ACM SIGCOMM Test of Time award 2006, CDAC-ACCS Foundation Award 2009, IISc Distinguished Alumnus Award 2014, WiMAX Forum Individual Contribution Award 2008, and ranks among the top 90 in Citeseer's list of Most Cited Authors in Computer Science. Dr. Jain is currently a Professor of Computer Science and Engineering at Washington University in St. Louis. Previously, he was one of the Co-founders of Nayna Networks, Inc - a next generation telecommunications systems company in San Jose, CA. He was a Senior Consulting Engineer at Digital Equipment Corporation in Littleton, Mass and then a professor of Computer and Information Sciences at Ohio State University in Columbus, Ohio. He is the author of ``Art of Computer Systems Performance Analysis,'' which won the 1991 ``Best-Advanced How-to Book, Systems'' award from Computer Press Association. His fourth book entitled " High-Performance TCP/IP: Concepts, Issues, and Solutions," was published by Prentice Hall in November 2003. He has recently co-edited "Quality of Service Architectures for Wireless Networks: Performance Metrics and Management," published in April 2010.

Further information about Dr. Jain including all his publications can be found at http://www.cse.wustl.edu/~jain/index.html.

Customer Reviews

Top Customer Reviews

Format: Hardcover
This seminal book was the most complete mainstream text on the subject when it was first published in 1991. The reason it remains popular eleven years later (which is an extraordinary life for a computer book) is because it's an applied mathematics book that focuses solely on performance analysis, simulation and measurements. Technology may change at a rapid pace, but the techniques for measuring it do not.
The book is broken into six parts consisting of 36 chapters and ten appendices. Part I is an overview of performance evaluation. I liked the chapter on common mistakes and how to avoid them, and the guidelines for selecting techniques and metrics.
Measurement techniques and tools are the focus of Part II. the eight chapters in this part address the full spectrum, including workload types, characterization techniques, capacity planning and benchmarking, and data presentation. Most of the chapters are generic enough to be timeless. The chapters covering execution monitors and accounting logs are showing their age, but the concepts are still valid. I especially liked the chapters about data presentation and ratios.
Part III is a refresher in statistics and probability, and can safely be skipped if your knowledge and skills are fresh. Part IV delves into experimental design and analysis, while Part V covers simulations. The remaining six chapters of the book, Part VI, are devoted to queuing models.
Note that although the math is clearly explained you need college level skills in order to fully comprehend the techniques presented. I recommend investing in MathCAD or a similar program to make it easy to work the exercises that end each chapter.
This book is one of the handful that will be on your bookshelf for years to come.
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Format: Hardcover
This is an absolute gem. I really think that this book must be read by every CS/EE engineer. Performance analysis is always something that comes as an afterthought and engineers think that some some "mathematical" guy called a perf analyst will stop by after the product is completed and analyze the product. This is def wrong. PA should be done at every stage of production.
This book has been written assuming a novice reader. Several parts of the book have to re-read to really understand what the author is trying to convey, but trust me you will really appreciate it.
I suggest reading the following parts of the book(in order):
Part I (whole)
Part II (4, 5, 6, browse {7,8}, 9, 10 ) 10 is cool stuff..impress your peers with this
Part III (whole) read, re-read, re-read till you have digested every line..worth it really!!!!
Part IV (whole) read, re-read, re-read till you have digested every line..worth it really!!!!
Part V : You can skip this if you are not into simulation.
Part VI : Not really that easy to follow. I suggest Gunter's book for this.
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By A Customer on November 27, 2001
Format: Hardcover Verified Purchase
I found this book by accident looking for some statistics help for a benchmarking project. It turned out to be worth its weight in gold as it is very clear, comphrehensive, and readable.
He outlines and elaborates a methodical, straightforward approach to performance analysis and provides excellent sections on what to do, not do, and how to validate or refute the analyses of others.
Extensive examples with solutions and enough equations to let you easily implement the analysis portions in code (or a spreadsheet if need be).
If you are doing any kind of performance analysis, whether it is for computer systems or not, you should get a copy.
The only reason I didnt give it 5 stars is a very small number of the example answers have typos or rounding errors. Be sure to get the errata list from the website.
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Format: Hardcover
While reading this book, I went back to my university years, and I realize mathematics can help a wide of real life situations.
As the author states, one of the common mistakes of recently graduated students is to think a real life easy problem with a complex mathematical model; I think one of the major problems with the IT mature professionals today, is that they try to solve complex problems following somekind of a deductive method; usually we override any kind of analysis because we think mathematical models or anything related is for university people....
While this book is very practical, it's also very impressive with it's mathematical rigour. For any performance consultant (database, server, network, etc) this book is very valuable guide for developing capacity planning and performance projects.
Don't expect to find very updated examples, but surely you won't need them if you understand the idea behind the concepts.
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Format: Hardcover
This book is a classic in its field. It covers performance analysis for computers, but is very easily extended to any area of performance analysis. It covers some theory, but mainly tips and "stories around the campfire" from those with a great deal of experience in the area. And that's actually more valuable than pure academic theory. The math is not too bad. One great feature is that you can focus on only those areas that you are concerned about and you can go as in-depth as you want. It's also true that it will never become obsolete (although some examples might be).
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