- Full Description
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.
- Table of Contents
Table of Contents
- Overview – Parallel Computing: Numerics, Applications, and Trends.
- Introduction to Parallel Computation.
- Tools for Parallel and Distributed Computing.
- Grid Computing.
- Parallel Structured Adaptive Mesh Refinement.
- Applications and Parallel Implementation of QMC Integration.
- Parallel Evolutionary Computation Framework for Single
- and Multiobjective Optimization.
- WaLBerla: Exploiting Massively Parallel Systems for Lattice Boltzmann Simulations.
- Parallel Pseudo
- spectral Methods for the Time Dependent Schrödinger Equation.
- Parallel Approaches in Molecular Dynamics Simulations.
- Parallel Computer Simulations of Heat Transfer in Biological Tissues.
- Parallel SVD Computing in the Latent Semantic Indexing Applications for Data Retrieval.
- Vector SIMD Parallelization in Signal Processing.
- Financial Applications: Parallel Portfolio Optimization.
- The Future of Parallel Computation.
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