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This book is an introduction to analytical performance modeling for computer systems, i.e., writing equations to describe their performance behavior. It is accessible to readers who have taken college-level courses in calculus and probability, networking, and operating systems. This is not a training manual for becoming an expert performance analyst. Rather, the objective is to help the reader construct simple models for analyzing and understanding the systems that they are interested in. Describing a complicated system abstractly with mathematical equations requires a careful choice of assumptions and approximations. They make the model tractable, but they must not remove essential characteristics of the system, nor introduce spurious properties. To help the reader understand the choices and their implications, this book discusses the analytical models for 40 research papers. These papers cover a broad range of topics: GPUs and disks, routers and crawling, databases and multimedia, worms and wireless, multicore and cloud, security and energy, etc. An appendix provides many questions for readers to exercise their understanding of the models in these papers.
This book is an introduction to analytical performance modeling for computer systems, i.e., writing equations to describe their performance behavior. It is accessible to readers who have taken college-level courses in calculus and probability, networking and operating systems. This is not a training manual for becoming an expert performance analyst. Rather, the objective is to help the reader construct simple models for analyzing and understanding the systems that they are interested in.
This book is an introduction to analytical performance modeling for computer systems, i.e., writing equations to describe their performance behavior. It is accessible to readers who have taken college-level courses in calculus and probability, networking, and operating systems. This is not a training manual for becoming an expert performance analyst. Rather, the objective is to help the reader construct simple models for analyzing and understanding the systems in which they are interested. Describing a complicated system abstractly with mathematical equations requires a careful choice of assumptions and approximations. These assumptions and approximations make the model tractable, but they must not remove essential characteristics of the system, nor introduce spurious properties. To help the reader understand the choices and their implications, this book discusses the analytical models in 20 research papers. These papers cover a broad range of topics: processors and disks, databases and multimedia, worms and wireless, etc. An Appendix provides some questions for readers to exercise their understanding of the models in these papers. Table of Contents: Preliminaries / Concepts and Little's Law / Single Queues / Open Systems / Markov Chains / Closed Systems / Bottlenecks and Flow Equivalence / Deterministic Approximations / Transient Analysis / Experimental Validation and Analysis / Analysis with an Analytical Model
Table of contents
This book describes methods to improve software performance and safety using advanced mathematical and computational analytics. The main focus is laid on the increase of software reliability by preventive and predictive maintenance with efficient usage of modern testing resources. The editors collect contributions from international researchers in the field.
Part I: An Overview of Performance Evaluation · Common Mistakes and How to Avoid Them· Selection of Techniques and Metrics· MEASUREMENT TECHNIQUES AND TOOLS· Types of Workloads· Workload Characterization Techniques· Monitors· Ratio GamesPart II: Probability Theory and Statistics · Summarizing Measured Data· Simple Linear Regression Models· Other Regression ModelsPart III: Experimental Design and Analysis · One-Factor Experiments· Two-Factor Full Factorial Design without Replications· Two-Factor Full Factorial Design with ReplicationsPart IV: Simulation· Analysis of Simulation Results· Testing Random-Number Generators· Commonly Used DistributionsPart V: Queuing Models· Analysis of a Single Queue· Operational Laws · Convolution Algorithm
Computer Performance Modeling Handbook
Addresses the major issues involved in computer design and architectures. Dealing primarily with theory, tools, and techniques as related to advanced computer systems, it provides tutorials and surveys and relates new important research results. Each chapter provides background information, describes and analyzes important work done in the field, and provides important direction to the reader on future work and further readings. The topics covered include hierarchical design schemes, parallel and distributed modeling and simulation, parallel simulation tools and techniques, theoretical models for formal and performance modeling, and performance evaluation techniques.
Computer system performance evaluation is a key discipline for the understanding of the behavior and limitations of large scale computer systems and networks. This volume provides an overview of the milestones and major developments of the field.The contributions to the book include many of the principal leaders from industry and academia with a truly international coverage, including several IEEE and ACM Fellows, two Fellows of the US National Academy of Engineering and a Fellow of the European Academy, and a former President of the Association of Computing Machinery.