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by James M. Ortega,Robert G. Voigt
Download Solution of Partial Differential Equations on Vector and Parallel Computers fb2
Mathematics
  • Author:
    James M. Ortega,Robert G. Voigt
  • ISBN:
    0898710553
  • ISBN13:
    978-0898710557
  • Genre:
  • Publisher:
    Society for Industrial and Applied Mathematics (January 1, 1987)
  • Pages:
    100 pages
  • Subcategory:
    Mathematics
  • Language:
  • FB2 format
    1335 kb
  • ePUB format
    1233 kb
  • DJVU format
    1842 kb
  • Rating:
    4.8
  • Votes:
    754
  • Formats:
    lrf lit mobi txt


Emphasis is on the solution of PDEs because these are typically the problems that generate high computational demands. The authors discuss architectural features of these computers insomuch as they influence algorithm performance, and provide insight into algorithm characteristics that allow effective use of hardware

Электронная книга "Solution of Partial Differential Equations on Vector and Parallel Computers", James M. Ortega, Robert G. Voigt.

Электронная книга "Solution of Partial Differential Equations on Vector and Parallel Computers", James M. Эту книгу можно прочитать в Google Play Книгах на компьютере, а также на устройствах Android и iOS. Выделяйте текст, добавляйте закладки и делайте заметки, скачав книгу "Solution of Partial Differential Equations on Vector and Parallel Computers" для чтения в офлайн-режиме.

Emphasis is on the solution of PDEs because these are typically the problems that generate high computational demands.

Solution of Partial Differential Equations on Vector and Parallel Computers Book Overview

Solution of Partial Differential Equations on Vector and Parallel Computers. by James M. Ortega and Robert G. Emphasis is on the solution of PDEs because these are typically the problems that generate high computational demands.

Main Author: Ortega, James . 1932-. Other Authors: Voigt, Robert G. Format: Book. MOL1D general purpose subroutine package for the numerical solution of partial differential equations, by: Hyman, James M. Published: (1979). Numerical solution of partial differential equations on parallel computers Published: (2006). Introduction to parallel and vector solution of linear systems, by: Ortega, James . 1932- Published: (1988).

Solution of Partial Differential Equations on Vector and Parallel Computers. SIAM REV. James M. Ortega. This paper presents a method for the solution of parabolic PDEs on parallel computers, which is a combination of implicit and explicit finite difference schemes based on a domain decomposition (DD) strategy. Moreover, this method is asynchronous (. no explicit synchronization is required among processors).

Certain pages from this book are designed for use in a group setting and. Chapter 1. Creativity and Problem Solving.

3 Nuclear Physics: Exploring the Heart of Matter. Ordinary and Partial Differential Equations An Introduction to Dynamical Systems John W. Cain, P. Frontiers in Massive Data Analysis. 59 MB·42,815 Downloads·New! to infer knowledge from massive data, and it characterizes seven major classes of computation. Certain pages from this book are designed for use in a group setting and. Load more similar PDF files.

The final paper (by Ortega, Voigt, and Romine) consists of an extensive bibliography on parallel and . Their main emphasis, however, was on the solution of partial differential equations on vector and parallel computers.

The final paper (by Ortega, Voigt, and Romine) consists of an extensive bibliography on parallel and vector numerical algorithms. Over 2,000 references, collected by the authors over a period of several years, are provided in this work. We also point to the textbook by Hockney and Jesshope which includes some material on programming linear algebra algorithms on parallel machines.

Partitioning and Dynamic Load Balancing for the Numerical Solution of Partial Differential Equations.

Since the dawn of computing, the quest for a better understanding of Nature has been a driving force for technological development. Groundbreaking achievements by great scientists have paved the way from the abacus to the supercomputing power of today. When trying to replicate Nature in the computer’s silicon test tube, there is need for precise and computable process descriptions. Partitioning and Dynamic Load Balancing for the Numerical Solution of Partial Differential Equations. Graphics Processor Units: New Prospects for Parallel Computing. Rumpf, Martin (et a.

This volume reviews, in the context of partial differential equations, algorithm development that has been specifically aimed at computers that exhibit some form of parallelism. Emphasis is on the solution of PDEs because these are typically the problems that generate high computational demands. The authors discuss architectural features of these computers in so much as they influence algorithm performance, and provide insight into algorithm characteristics that allow effective use of hardware.