Software Performance and Scalability (eBook)

A Quantitative Approach

Henry H. Liu (Autor)

eBook Download: PDF | EPUB

2009 | 1. Auflage
396 Seiten
John Wiley & Sons (Verlag)
978-0-470-46538-7 (ISBN)

Infos

Praise from the Reviewers:

"The practicality of the subject in a real-world situation
distinguishes this book from others available on the market."

--Professor Behrouz Far, University of Calgary

"This book could replace the computer organization texts now in
use that every CS and CpE student must take. . . . It is much
needed, well written, and thoughtful."

--Professor Larry Bernstein, Stevens Institute of
Technology

A distinctive, educational text onsoftware performance and
scalability

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--helps you learn 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 level

Software Performance and Scalability gives you a
specialized skill set that will enable you to design and build
performance into your products with immediate, measurable
improvements. Complemented with real-world case studies, it is an
indispensable resource for software developers, quality and
performance assurance engineers, architects, and managers. It is
anideal text for university courses related to computer and
software performance evaluation and can also be used to supplement
a course in computer organization or in queuing theory for
upper-division and graduate computer science students.

Autor

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.

Inhalt

Preface.

Acknowledgments.

Introduction: Performance versus Scalability.

PART 1 THE BASICS.

1 Hardware Platform.

1.1 Turning Machine.

1.2 von Neumann Machine.

1.3 Zuse Machine.

1.4 Intel Machine.

1.5 Sun Machine.

1.6 System Under Test.

1.7 Odds Against Turing.

1.8 Sizing Hardware.

1.9 Summary.

Recommended Reading.

Exercises.

2 Software Platform.

2.1 Software Stack.

2.2 APIs.

2.3 Multithreading.

2.4 Categorizing Software.

2.5 Enterprise Computing.

2.6 Summary.

Recommended Reading.

Exercises.

3 Testing Software Performance and Scalability.

3.1 Scope of Software Performance and Scalability Testing.

3.2 Software Development Performance.

3.3 Defining Software Performance.

3.4 Stochastic Nature of Software Performance Measurements.

3.5 Amdahl's Law.

3.6 Software Performance and Scalability Factors.

3.7 System Performance Counters.

3.8 Software Performance Data Principles.

3.9 Summary.

Recommended Reading.

Exercises.

PART 2 APPLYING QUEUING THEORY.

4 Introduction to Queuing Theory.

4.1 Queuing Concepts and Metrics.

4.2 Introduction to Probability Theory.

4.3 Applying Probability Theory to Queuing Systems.

4.4 Queuing Models for Networked Queuing Systems.

4.5 Summary.

Recommended Reading.

Exercises.

5 Case Study I: Queuing Theory to SOA.

5.1 Introduction to SOA.

5.2 XML Web Services.

5.3 The Analytical Model.

5.4 Service Demand.

5.5 MedRec Application.

5.6 MedRec Deployment and Test Scenario.

5.7 Test Results.

5.8 Comparing the Model with the Measurements.

5.9 Validity of the SOA Performance Model.

5.10 Summary.

Recommended Reading.

Exercises.

6 Caser Study II: Queuing Theory Applied to Optimizing and Tuning Software Performance and Scalability.

6.1 Analyzing Software Performance and Scalability.

6.2 Effective Optimization and Tuning Techniques.

6.3 Balanced Queuing System.

6.4 Summary.

Recommended Reading.

Exercises.

PART 3 APPLYING API PROFILING.

7 Defining API Profiling Framework.

7.1 Defense Lines Against Software Performance and Scalability Defects.

7.2 Software Program Execution Stack.

7.3 The PerfBasic API Profiling Framework.

7.4 Summary.

Exercises.

8 Enabling API Profiling Framework.

8.1 Overall Structure.

8.2 Global Parameters.

8.3 Main Logic.

8.4 Processing Files.

8.5 Enabling Profiling.

8.6 Processing Inner Classes.

8.7 Processing Comments.

8.8 Processing Methods Begin.

8.9 Processing Return Statements.

8.10 Processing Method End.

8.11 Processing Main Method.

8.12 Test Program.

8.13 Summary.

Recommended Reading.

Exercises.

9. Implementing API Profiling Framework.

9.1 Graphics Tool--dot.

9.2 Graphics Tool--ILOG.

9.3 Graphics Resolution.

9.4 Implementation.

9.5 Summary.

Exercises.

10 Case Study: Applying API Profiting to Solving Software Performance and Scalability Challenges.

10.1 Enabling API Profiling.

10.2 API Profiling with Standard Logs.

10.3 API Profiling with Custom Logs.

10.4 API Profiling with Combo Logs.

10.5 Applying API Profiling to Solving Performance and Scalability Problems.

10.6 Summary.

Exercises.

APPENDIX A STOCHASTIC EQUILIBRIUM AND ERGODICITY.

A.1 Basic Concepts.

A.2 Classification of Random Processes.

A.3 Discrete-Time Markov Chains.

A.4 Continuous-Time Markov Chains.

A.5 Stochastic Equilibrium and Ergodicity.

A.6 Birth-Death Chains.

APPENDIX B MEMORYLESS PROPERTY OF THE EXPONENTIAL DISTRIBUTION.

APPENDIX C M/M/1 QUEUES AT STEADY STATE.

C.1 Review of Birth-Death Chains.

C.2 Utilization and Throughput.

C.3 Average Queue Length in the System.

C.4 Average System Time.

C.5 Average Wait Time.

Produkt-Details

• Erscheint lt. Verlag: 20.9.2011
• Reihe/Serie: Quantitative Software Engineering Series
• Reihe/Serie: Quantitative Software Engineering Series
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge
• Themenwelt: Mathematik / Informatik ► Informatik ► Software Entwicklung
• Schlagworte: Computer Science • Database & Data Warehousing Technologies • Datenbanken u. Data Warehousing • Informatik • Performance-Optimierung • Programmierung u. Software-Entwicklung • Programming & Software Development • Software engineering • Software-Engineering • Softwareentwicklung
• ISBN-10: 0-470-46538-7 / 0470465387
• ISBN-13: 978-0-470-46538-7 / 9780470465387