Synopses & Reviews
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. Features: • 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.
Review
From the reviews: "This is collection of 15 chapters, mostly on topics related to numerical computation ... . The target audience consists of researchers, practitioners, and students. ... The typesetting is of high quality, and there many well-rendered mathematical problems on display. ... the book includes a tantalizingly short introduction to quantum computing. ... this could become a worthwhile first approach to a new computing paradigm ... . Again the included references will help those interested in the subject." (A. Squassabia, ACM Computing Reviews, February, 2010)
Synopsis
This book targets development of efficient parallel computational methods for different scientific and technical applications. Readers who wish to design and implement efficient solutions on parallel and distributed computer systems are given insight into the theory of the computational methods through practical application being emphasized throughout. Features: Discusses development of algorithms for different applications plus other aspects related to parallel numerical solution of PDEs (e.g. grid refinement). Considers other numerical applications such as data retrieval by linear algebra approach and quasi Monte-Carlo methods. Covers molecular dynamics, computational quantum physics, analysis of bio-signals and image and video coding. Chapters overviews and conclusions with a discussion on future work. This concise volume provides the state-of-the-art in parallel and distributed computing, and is a must-read for practitioners, researchers and graduate students.
Synopsis
The use of parallel programming and architectures is essential for simulating and solving problems in modern computational practice. There has been rapid progress in microprocessor architecture, interconnection technology and software devel- ment, which are in?uencing directly the rapid growth of parallel and distributed computing. However, in order to make these bene?ts usable in practice, this dev- opment must be accompanied by progress in the design, analysis and application aspects of parallel algorithms. In particular, new approaches from parallel num- ics are important for solving complex computational problems on parallel and/or distributed systems. The contributions to this book are focused on topics most concerned in the trends of today's parallel computing. These range from parallel algorithmics, progr- ming, tools, network computing to future parallel computing. Particular attention is paid to parallel numerics: linear algebra, differential equations, numerical integ- tion, number theory and their applications in computer simulations, which together form the kernel of the monograph. We expect that the book will be of interest to scientists working on parallel computing, doctoral students, teachers, engineers and mathematicians dealing with numerical applications and computer simulations of natural phenomena.
Synopsis
This concise volume provides the state-of-the-art in parallel and distributed computing. Written by internationally renowned experts, it targets development of efficient parallel computational methods for different scientific and technical applications.
Table of Contents
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 Thomas Fahringer Grid 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 Roman Trobec Parallel SVD Computing in the Latent Semantic Indexing Applications for Data Retrieval Gabriel Okša and Marián Vajteršic Short-Vector SIMD Parallelization in Signal Processing Rade Kutil Financial Applications: Parallel Portfolio Optimization Andreas Grothey The Future of Parallel Computation Selim G. Akl and Marius Nagy