Mathematics for Large Scale Computing

Regular price €310.00
Adaptive Algorithms
algorithm development
Alternating Direction Method
Approximate Inverse
asymptotic-induced technique
Backward Difference Scheme
Black Oil Model
Broyden's update formula
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Collocation Equations
Collocation Methods
Column Decomposition
Domain Decomposition
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Finite Difference Methods
Gray Codes
Higher Order Difference Schemes
Homogeneous Dirichlet Boundary Conditions
Incomplete LU Factorization
linear advection equations
Linear Parabolic Problem
mathematical issues
Matrix Vector Multiplication
Mixed Finite Element Approximation
Optimal Order Error Estimates
Ordinary Differential Equations
Positive Definite Symmetric Linear System
Priori Error Bounds
Spline Collocation Methods
Step Ii
Superconvergence Results
Tri-diagonal Matrix

Product details

  • ISBN 9780824781224
  • Weight: 635g
  • Dimensions: 210 x 280mm
  • Publication Date: 28 Jul 1989
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Paperback
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During recent years a great deal of interest has been devoted to large scale computing applications. This has occurred in great part because of the introduction of advanced high performance computer architectures. The book contains survey articles as well as chapters on specific research applications, development and analysis of numerical algorithms, and performance evaluation of algorithms on advanced architectures. The effect of specialized architectural features on the performance of large scale computation is also considered by several authors. Several areas of applications are represented, including the numerical solution of partial differential equations, iterative techniques for large structured problems, the numerical solution of boundary value problems for ordinary differential equations, numerical optimization, and numerical quadrature. Mathematical issues in computer architecture are also presented, including the description of grey codes for generalized hypercubes. The results presented in this volume give, in our opinion, a representative picture of today’s state of the art in several aspects of large scale computing.
Julio Diaz, Center for Parallel and Scientific Computing The university of Tulsa, Tulsa, Oklahoma, USA.