Performance Evaluation, Prediction and Visualization of Parallel Systems

  • Xingfu Wu

Table of contents

  1. Front Matter
    Pages i-xxii
  2. Xingfu Wu
    Pages 1-34
  3. Xingfu Wu
    Pages 35-63
  4. Xingfu Wu
    Pages 65-101
  5. Xingfu Wu
    Pages 163-191
  6. Xingfu Wu
    Pages 193-248
  7. Xingfu Wu
    Pages 249-279
  8. Back Matter
    Pages 313-319

About this book


Performance Evaluation, Prediction and Visualization in Parallel Systems presents a comprehensive and systematic discussion of theoretics, methods, techniques and tools for performance evaluation, prediction and visualization of parallel systems. Chapter 1 gives a short overview of performance degradation of parallel systems, and presents a general discussion on the importance of performance evaluation, prediction and visualization of parallel systems. Chapter 2 analyzes and defines several kinds of serial and parallel runtime, points out some of the weaknesses of parallel speedup metrics, and discusses how to improve and generalize them. Chapter 3 describes formal definitions of scalability, addresses the basic metrics affecting the scalability of parallel systems, discusses scalability of parallel systems from three aspects: parallel architecture, parallel algorithm and parallel algorithm-architecture combinations, and analyzes the relations of scalability and speedup. Chapter 4 discusses the methodology of performance measurement, describes the benchmark- oriented performance test and analysis and how to measure speedup and scalability in practice. Chapter 5 analyzes the difficulties in performance prediction, discusses application-oriented and architecture-oriented performance prediction and how to predict speedup and scalability in practice. Chapter 6 discusses performance visualization techniques and tools for parallel systems from three stages: performance data collection, performance data filtering and performance data visualization, and classifies the existing performance visualization tools. Chapter 7 describes parallel compiling-based, search-based and knowledge-based performance debugging, which assists programmers to optimize the strategy or algorithm in their parallel programs, and presents visual programming-based performance debugging to help programmers identify the location and cause of the performance problem. It also provides concrete suggestions on how to modify their parallel program to improve the performance. Chapter 8 gives an overview of current interconnection networks for parallel systems, analyzes the scalability of interconnection networks, and discusses how to measure and improve network performances.
Performance Evaluation, Prediction and Visualization in Parallel Systems serves as an excellent reference for researchers, and may be used as a text for advanced courses on the topic.


Scala algorithms interconnection networks linear optimization metrics network programming visual programming

Authors and affiliations

  • Xingfu Wu
    • 1
    • 2
  1. 1.Department of Computer ScienceLouisiana State UniversityUSA
  2. 2.State Key Laboratory for Novel Software Technology at Nanjing UniversityChina

Bibliographic information

  • DOI
  • Copyright Information Kluwer Academic Publishers 1999
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-7343-8
  • Online ISBN 978-1-4615-5147-8
  • Series Print ISSN 1566-0710
  • Buy this book on publisher's site
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