investigation of preconditioners suitable for parallel implementation
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investigation of preconditioners suitable for parallel implementation by C.A Rostron

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Published by UMIST in Manchester .
Written in English


Book details:

Edition Notes

StatementC.A. Rostron ; supervised by R.W. Thatcher.
ContributionsThatcher, R.W., Mathematics.
ID Numbers
Open LibraryOL21239365M

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@article{osti_, title = {The Design and Implementation of hypre, a Library of Parallel High Performance Preconditioners}, author = {Falgout, R D and Jones, J E and Yang, U M}, abstractNote = {The increasing demands of computationally challenging applications and the advance of larger more powerful computers with more complicated architectures have necessitated the development of new. original preconditioners would appear suitable for effective parallel implementation, although such implementation details have not been explored before. That the original preconditioner leads to a small number of iterations, which is independent of the number of time-steps when employed with the widely used GMRES method [12], is established in [11]. We describe and test spai , a parallel MPI implementation of the Sparse Approximate Inverse (SPAI) preconditioner. We show that SPAI can be very effective for solving a set of very large and.   () Parallel Implementation and Practical Use of Sparse Approximate Inverse Preconditioners with a Priori Sparsity Patterns. The International Journal of High Performance Computing Applications ,

The Design and Implementation of hypre, a Library of Parallel High Performance Preconditioners t,,andUlrikeMeierYang.   This motivates the investigation of space decomposition preconditioners,,, which are efficient and suitable for parallel implementation. These preconditioners exist in additive, multiplicative and combined hybrid forms. All variants require solution of sub-problems defined on individual sub-spaces of the considered space decomposition. Design and implementation issues that concern the development of a package of parallel algebraic two-level Schwarz preconditioners are discussed. The computations are based on the Parallel Sparse. The resulting algorithms are well suited for implementation on computers with parallel architecture. In this paper, we will develop a technique which utilizes these earlier methods to derive even more efficient preconditioners. The itera-tive algorithms using these new preconditioners converge to .

Parallel implementation. As already stated, 3-D EM problems are typically large-scale problems whose solutions require enormous amounts of computation. Nowadays, parallel computing has been widely accepted as a means of handling very large and demanding computational tasks. for parallel implementation as shown by Grote and Huckle [9], and Chow [8]. However, preconditioning quality may lag that of ICT preconditioners. Incomplete Cholesky with Selective Inversion Our parallel incomplete Cholesky with SI uses many of the ideas from parallel sparse direct multifrontal solution. We start with a good ll-reducing. preconditioners are defined as a sum of independent operators on a sequence of nested subspaces of the full approximation space. On a parallel computer, the evaluation of these operators and hence of the preconditioner on a given function can be computed concurrently. We shall study this new technique for developing preconditioners first in.   Abstract. We describe the implementation and performance of a novel class of preconditioners. These preconditioners were proposed and theoretically analyzed by Pravin Vaidya in , but no report on their implementation or performance in practice has ever been published.