Trobec, Roman, Vajteršic, Marián, Zinterhof, Peter (Eds.)
2009, XXIV, 520 p.
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Focuses on development of efficient parallel computational methods with a practical emphasis, thereby conveying a deeper understanding to the reader
Written by internationally renowned experts, this volume provides readers with a concise reading of the state-of-the-art on the topic
Advancements in microprocessor architecture, interconnection technology, and software development have fueled rapid growth in parallel and distributed computing. However, this development is only of practical benefit if it is accompanied by progress in the design, analysis and application aspects of parallel algorithms. In particular, new approaches from parallel numerics are important for solving complex computational problems on parallel and/or distributed systems.
This concise survey presents the latest achievements in parallel and distributed computing. The editors emphasize presentation of the theoretical discussion of each method in the context of its application, with particular focus applied to the subject of modeling physical phenomena by partial differential equations (PDEs), including the development of algorithms for different applications (such as financial prediction, and medical simulations).
Internationally renowned experts in the field provide contributions focusing on topics relating to the latest trends in parallel computing. These range from parallel algorithmics, programming, tools, and network computing to future parallel computing. Particular attention is paid to parallel numerics: linear algebra, differential equations, numerical integration, number theory, and their application in computer simulations.
• Presents a comprehensive introductory chapter, outlining advances and trends in parallelism
• Discusses the development of algorithms for different applications, plus other aspects related to the parallel numerical solution of PDEs
• Investigates other numerical applications, such as data retrieval by linear algebra approach, and quasi-Monte Carlo methods
• Explores molecular dynamics, computational quantum physics, the analysis of biosignals, and image and video coding
• Provides helpful overviews and conclusions for all chapters
• Concludes with a thorough chapter on the future of parallel computing
This invaluable text/reference presents the state of the art in parallel and distributed computing. The book is a must-read for all scientists who wish to design and implement efficient solutions on parallel and distributed computer systems, as well as for mathematicians dealing with numerical applications and computer simulations of natural phenomena.
Dr. Roman Trobec is an Assistant Professor at the Department of Communication Systems of the Jozef Stefan institute, Slovenia.
Dr. Marian Vajteršic and Dr. Peter Zinterhof are Professors at the Department of Computer Sciences of the University of Salzburg, Austria.
Overview – Parallel Computing: Numerics, Applications, and Trends
Marián Vajteršic, Peter Zinterhof and Roman Trobec
Introduction to Parallel Computation
Selim G. Akl and Marius Nagy
Tools for Parallel and Distributed Computing
Uroš Cibej, Anthony Sulistio and Rajkumar Buyya
Parallel Structured Adaptive Mesh Refinement
Jarmo Rantakokko and Michael Thuné
Applications and Parallel Implementation of QMC Integration
Peter Jez, Andreas Uhl and Peter Zinterhof
Parallel Evolutionary Computation Framework for Single- and Multiobjective Optimization
Bogdan Filipic and Matjaž Depolli
WaLBerla: Exploiting Massively Parallel Systems for Lattice Boltzmann Simulations
Christian Feichtinger, Jan Götz, Stefan Donath, Klaus Iglberger and Ulrich Rüde
Parallel Pseudo-spectral Methods for the Time Dependent Schrödinger Equation
Tore Birkeland and Tor Sørevik
Parallel Approaches in Molecular Dynamics Simulations
Dušanka Janežic, Urban Borštnik and Matej Praprotnik
Parallel Computer Simulations of Heat Transfer in Biological Tissues
Parallel SVD Computing in the Latent Semantic Indexing Applications for Data Retrieval
Gabriel Okša and Marián Vajteršic
Short-Vector SIMD Parallelization in Signal Processing
Financial Applications: Parallel Portfolio Optimization
The Future of Parallel Computation
Selim G. Akl and Marius Nagy