Algorithmic bombardment for the iterative solution of linear systems: a poly-iterative approach
TL;DR: Here three algorithms simultaneously are applied simultaneously to the system, in the hope that at least one will converge to the solution, and the cost of three methods can be reduced to that of a single method.
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About: This article is published in Journal of Computational and Applied Mathematics. The article was published on 05 Nov 1996. and is currently open access. The article focuses on the topics: Iterative method & Solver.
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Citations
Self-Adapting Numerical Software for Next Generation Applications
Jack Dongarra,Victor Eijkhout +1 more
- 01 May 2003
TL;DR: SANS innovations will provide to the scientific and engineering community a dynamic computational environment in which the most effective library components are automatically selected based on the problem characteristics, data attributes, and the state of the grid.
Self-adapting software for numerical linear algebra and LAPACK for clusters
Zizhong Chen,Jack Dongarra,Piotr Luszczek,Kenneth Roche +3 more
- 01 Nov 2003
TL;DR: The context, design, and recent development of the LAPACK for clusters (LFC) project is described, developed in the framework of Self-Adapting Numerical Software (SANS), which believes such an approach can deliver the convenience and ease of use of existing sequential environments bundled with the power and versatility of highly tuned parallel codes that execute on clusters.
Algorithmic bombardment for the iterative solution of linear systems: a poly-iterative approach
TL;DR: Here three algorithms simultaneously are applied simultaneously to the system, in the hope that at least one will converge to the solution, and the cost of three methods can be reduced to that of a single method.
35
The quest for petascale computing
Jack Dongarra,David W. Walker +1 more
TL;DR: Petascale computing is capable of driving the next decade of research in high-performance computing and communications and will require advances across all aspects of it.
35
Recursive approach in sparse matrix LU factorization
TL;DR: In this paper, a recursive method for the LU factorization of sparse matrices is described, and performance results show that the recursive approach may perform comparable to leading software packages for sparse matrix factorization in terms of execution time, memory usage and error estimates of the solution.
References
GMRES: a generalized minimal residual algorithm for solving nonsymmetric linear systems
Youcef Saad,Martin H. Schultz +1 more
TL;DR: An iterative method for solving linear systems, which has the property of minimizing at every step the norm of the residual vector over a Krylov subspace.
Methods of Conjugate Gradients for Solving Linear Systems
TL;DR: An iterative algorithm is given for solving a system Ax=k of n linear equations in n unknowns and it is shown that this method is a special case of a very general method which also includes Gaussian elimination.
BI-CGSTAB: a fast and smoothly converging variant of BI-CG for the solution of nonsymmetric linear systems
TL;DR: Numerical experiments indicate that the new variant of Bi-CG, named Bi- CGSTAB, is often much more efficient than CG-S, so that in some cases rounding errors can even result in severe cancellation effects in the solution.
5.5K
•Book
Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods
Richard Barrett
- 01 Jan 1987
TL;DR: In this book, which focuses on the use of iterative methods for solving large sparse systems of linear equations, templates are introduced to meet the needs of both the traditional user and the high-performance specialist.
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
TL;DR: The PVM system, a heterogeneous network computing trends in distributed computing PVM overview other packages, and troubleshooting: geting PVM installed getting PVM running compiling applications running applications debugging and tracing debugging the system.
2.1K
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