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.
