Analyzing Computer Systems Performance: With Perl: PDQ

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9783540208655: Analyzing Computer Systems Performance: With Perl: PDQ
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Makes performance analysis and queueing theory concepts simple to understand and available to anyone with a background in high school algebra


Presents the practical application of these concepts in the context of modern, distributed, computer system designs

Packed with helpful examples that are based on the author's experience analyzing the performance of large-scale systems over the past 20 years.

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About the Author:

 

Neil Gunther, M.Sc., Ph.D. is a leading industry computer performance consultant who founded Performance Dynamics Company (www.perfdynamics.com) in 1994. Prior to that, Dr. Gunther held research and management positions at San Jose State University, JPL/NASA (Voyager and Galileo spacecraft), Xerox PARC research center and Pyramid/Siemens Technology. His performance and capacity planning classes have been presented at such organizations as Boeing, Fedex, Motorola, Stanford University, and Sun Microsystems.

Dr. Gunther is the author of over a hundred papers on computer performance topics, including "HIT-AND-RUN TACTICS ENABLE GUERRILLA CAPACITY PLANNING," published recently in IEEE IT Professional magazine. He has also written the book THE PRACTICAL PERFORMANCE ANALYST (iUniverse.com 2000). In 1996 he was awarded Best Technical Paper at CMG, and in 1997 was nominated for the A.A. Michelson Award. Dr. Gunther is a member of the AMS, ACM, CMG, IEEE, SAGE-AU, SIGMETRICS and USENIX.

Review:

From the reviews:

"The literature of computer performance analysis is generally composed of two groups: heavy theoretical treatises and performance cookbooks. ... Surprisingly, this book is exceptionally well balanced between theory and practice ... . I strongly recommend this book, both for the novice practitioner and for the experienced performance analyst. Both can extract a vast array of benefits, ranging from understanding the theoretical concepts of performance modeling, to building for themselves a powerful modeling tool ... ." (Jair Merlo, Computing Reviews, May, 2005)

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