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Computer Science - Communication Networks | Parallel Computing - Numerics, Applications, and Trends

Parallel Computing

Numerics, Applications, and Trends

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.

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.

Content Level » Research

Keywords » Computer - Computing Clusters - Financial Applications - Heat Transfer - MPI Llibrary - Mesh Refinement - Molecular Dynamics - Numerical Simulation - Parallel Computing - Quasi Monte-Carlo Techniques - Scientific Computing - Simulation - algorithms - distributed computing - optimization

Related subjects » Communication Networks - Computational Science & Engineering - Theoretical Computer Science

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

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