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9780470462539

Software Performance and Scalability A Quantitative Approach

by
  • ISBN13:

    9780470462539

  • ISBN10:

    0470462531

  • Edition: 1st
  • Format: Hardcover
  • Copyright: 2009-05-26
  • Publisher: Wiley-Blackwell
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Supplemental Materials

What is included with this book?

Summary

This is the first book to take a quantitative approach to the subject of software performance and scalability. It brings together three unique perspectives to demonstrate how your products can be optimized and tuned for the best possible performance and scalability:- The Basics-introduces the computer hardware and software architectures that predetermine the performance and scalability of a software product as well as the principles of measuring the performance and scalability of a software product- Queuing Theory-explains the performance laws and queuing models for interpreting the underlying physics behind software performance and scalability, supplemented with ready-to-apply techniques for improving the performance and scalability of a software system- API Profiling-shows you how to design more efficient algorithms and achieve optimized performance and scalability, aided by adopting an API profiling framework (perfBasic) built on the concept of a performance map for drilling down performance root causes at the API levelThis book gives a specialized skill set that enables you to design and build performance into your products with immediate, measurable improvements. Complemented with real-world case studies, this is an indispensable resource for software developers, quality and performance assurance engineers, architects, and managers. It is an ideal text for university courses related to computer and software performance evaluation, computer organization, and queuing theory.

Author Biography

Henry H. Liu, PhD, is Software Developer at BMC Software. Previously, he worked as a physicist in the national labs of China, France, Germany, and the United States. He also worked at Intel and Amdocs as a software performance engineer prior to joining BMC. He was an Alexander von Humboldt Research Fellow from 1990–1992 in Germany. He was awarded the Best Paper Award at CMG's 2004 conference in the category of software performance engineering. He is a certified Sun Enterprise Architect, IBM XML Developer, and Microsoft .NET Developer. Dr. Liu is most interested in applying his previous scientific research disciplines to solving software performance and scalability challenges.

Table of Contents

Preface
Acknowledgments
Introduction: Performance versus Scalability
The Basics
Hardware Platform
Turning Machine
von Neumann Machine
Zuse Machine
Intel Machine
Sun Machine
System Under Test
Odds Against Turing
Sizing Hardware
Summary
Recommended Reading
Exercises
Software Platform
Software Stack
APIs
Multithreading
Categorizing Software
Enterprise Computing
Summary
Recommended Reading
Exercises
Testing Software Performance and Scalability
Scope of Software Performance and Scalability Testing
Software Development Performance
Defining Software Performance
Stochastic Nature of Software Performance Measurements
Amdahl's Law
Software Performance and Scalability Factors
System Performance Counters
Software Performance Data Principles
Summary
Recommended Reading
Exercises
Applying Queuing Theory
Introduction to Queuing Theory
Queuing Concepts and Metrics
Introduction to Probability Theory
Applying Probability Theory to Queuing Systems
Queuing Models for Networked Queuing Systems
Summary
Recommended Reading
Exercises
Case Study I: Queuing Theory to SOA
Introduction to SOA
XML Web Services
The Analytical Model
Service Demand
MedRec Application
MedRec Deployment and Test Scenario
Test Results
Comparing the Model with the Measurements
Validity of the SOA Performance Model
Summary
Recommended Reading
Exercises
Caser Study II: Queuing Theory Applied to Optimizing and Tuning Software Performance and Scalability
Analyzing Software Performance and Scalability
Effective Optimization and Tuning Techniques
Balanced Queuing System
Summary
Recommended Reading
Exercises
Applying Api Profiling
Defining API Profiling Framework
Defense Lines Against Software Performance and Scalability Defects
Software Program Execution Stack
The PerfBasic API Profiling Framework
Summary
Exercises
Enabling API Profiling Framework
Overall Structure
Global Parameters
Main Logic
Processing Files
Enabling Profiling
Processing Inner Classes
Processing Comments
Processing Methods Begin
Processing Return Statements
Processing Method End
Processing Main Method
Test Program
Summary
Recommended Reading
Exercises
Implementing API Profiling Framework
Graphics Tool-dot
Graphics Tool-ILOG
Graphics Resolution
Implementation
Summary
Exercises
Case Study: Applying API Profiting to Solving Software Performance and Scalability Challenges
Enabling API Profiling
API Profiling with Standard Logs
API Profiling with Custom Logs
API Profiling with Combo Logs
Applying API Profiling to Solving Performance and Scalability Problems
Summary
Exercises
Stochastic Equilibrium and Ergodicity
Basic Concepts
Classification of Random Processes
Discrete-Time Markov Chains
Continuous-Time Markov Chains
Stochastic Equilibrium and Ergodicity
Birth-Death Chains
Memoryless Property of The Exponential Distribution
M/M/1 Queues at Steady State
Review of Birth-Death Chains
Utilization and Throughput
Average Queue Length in the System
Average System Time
Average Wait Time
Table of Contents provided by Publisher. All Rights Reserved.

Supplemental Materials

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The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.

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