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by Xingfu Wu
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Hardware & DIY
  • Author:
    Xingfu Wu
  • ISBN:
    0792384628
  • ISBN13:
    978-0792384625
  • Genre:
  • Publisher:
    Springer; 1999 edition (February 28, 1999)
  • Pages:
    319 pages
  • Subcategory:
    Hardware & DIY
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    1153 kb
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    4.1
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Parallel Performance Prediction.

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. Parallel Performance Prediction.

Parallel Performance Parallel Program Parallel System Visualization Tool Program Execution. In: Performance Evaluation, Prediction and Visualization of Parallel Systems

Parallel Performance Parallel Program Parallel System Visualization Tool Program Execution. Xingfu Wu and Wei Li, Visualizing the Network Activity among Node Processors, In: Proc. of International Symposium on Transmission & Switching New Technology (ISTST96), China, Sep’. In: Performance Evaluation, Prediction and Visualization of Parallel Systems. Publisher Name Springer, Boston, MA.

Performance Evaluation, Prediction and Visualization of Parallel Systems. Performance Evaluation, Prediction and Visualization of Parallel Systems pp 281-312 Cite as. Performance Evaluation of Interconnection Networks for Parallel Systems. Authors and affiliations. Heath, Recent development and case studies in performance visualization using ParaGraph, Performance Measurement and Visualization of Parallel Systems, Ed. G. Haring and G. Kotsis, Elsevier Science Publishers B. 1993.

In: Performance Evaluation, Prediction and Visualization of Parallel Systems

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves. Xingfu Wu and Wei Li, Performance models for scalable cluster computing, Journal of Systems Architecture, Vol. 44, No. 3, Elsevier Science Publishers . The Kluwer International Series on Asian Studies in Computer and Information Science, vol 4. Springer, Boston, MA.

Xingfu Wu. ISBN: 0792384628 . Chapter1 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

Xingfu Wu. Chapter1 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.

Performance Evaluation of Interconnection Networks for Parallel systems. oceedings{Wu1999PerformanceEP, title {Performance Evaluation, Prediction and Visualization of Parallel Systems}, author {Xingfu Wu}, booktitle {The Kluwer International Series on Asian Studies in Computer and Information Science}, year {1999} }. Xingfu Wu. Published in. The Kluwer International Series on Asian Studie. 999.

Автор: Xingfu Wu Название: Performance Evaluation, Prediction and Visualization of. .

This book focuses on distributed memory multiprocessor systems, and introduces an approach for predicting the performance parameters of parallel programs, including work distribution, number of transfers, and amount of data transferred.

Systems Architecture Books. International Series on Asian Studies in Computer and Inform. General System Architecture Books. Performance Evaluation, Prediction and Visualization of Parallel Systems. This button opens a dialog that displays additional images for this product with the option to zoom in or out. Tell us if something is incorrect.

Performance evaluation, prediction and visualization of parallel systems, ser. the international series . We start by considering the different types of workload models that are typically used in performance evaluation studies. the international series on asian studies in computer and information science. X Wu. Software Reliability Analysis Considering the Fault Detection Trends for Big Data on Cloud Computing. We then discuss performance measurement techniques, including platform benchmarking, application profiling, and system load testing. Following this, we survey the most common methods and techniques for performance modeling of software systems.

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.