Workload Modeling for Computer Systems Performance Evaluation

Nonfiction, Computers, Computer Hardware, Input-Output Equipment, Science & Nature, Mathematics, General Computing
Cover of the book Workload Modeling for Computer Systems Performance Evaluation by Dror G. Feitelson, Cambridge University Press
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Author: Dror G. Feitelson ISBN: 9781316235096
Publisher: Cambridge University Press Publication: March 23, 2015
Imprint: Cambridge University Press Language: English
Author: Dror G. Feitelson
ISBN: 9781316235096
Publisher: Cambridge University Press
Publication: March 23, 2015
Imprint: Cambridge University Press
Language: English

Reliable performance evaluations require the use of representative workloads. This is no easy task since modern computer systems and their workloads are complex, with many interrelated attributes and complicated structures. Experts often use sophisticated mathematics to analyze and describe workload models, making these models difficult for practitioners to grasp. This book aims to close this gap by emphasizing the intuition and the reasoning behind the definitions and derivations related to the workload models. It provides numerous examples from real production systems, with hundreds of graphs. Using this book, readers will be able to analyze collected workload data and clean it if necessary, derive statistical models that include skewed marginal distributions and correlations, and consider the need for generative models and feedback from the system. The descriptive statistics techniques covered are also useful for other domains.

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Reliable performance evaluations require the use of representative workloads. This is no easy task since modern computer systems and their workloads are complex, with many interrelated attributes and complicated structures. Experts often use sophisticated mathematics to analyze and describe workload models, making these models difficult for practitioners to grasp. This book aims to close this gap by emphasizing the intuition and the reasoning behind the definitions and derivations related to the workload models. It provides numerous examples from real production systems, with hundreds of graphs. Using this book, readers will be able to analyze collected workload data and clean it if necessary, derive statistical models that include skewed marginal distributions and correlations, and consider the need for generative models and feedback from the system. The descriptive statistics techniques covered are also useful for other domains.

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