|
Showing 1 - 2 of
2 matches in All Departments
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.
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.
|
You may like...
The Estate
Liza Costello
Paperback
R379
Discovery Miles 3 790
Lone Wolf
Gregg Hurwitz
Paperback
R380
R297
Discovery Miles 2 970
Doolhof
Rudie van Rensburg
Paperback
R365
R314
Discovery Miles 3 140
Eruption
Michael Crichton, James Patterson
Paperback
R380
R270
Discovery Miles 2 700
Camino Ghosts
John Grisham
Paperback
R450
R299
Discovery Miles 2 990
Forget Me Not
M. J. Arlidge
Paperback
R425
R285
Discovery Miles 2 850
Suspects
Danielle Steel
Paperback
(3)
R340
R292
Discovery Miles 2 920
Daylight
David Baldacci
Paperback
(2)
R365
R314
Discovery Miles 3 140
|