Block jacobi preconditioning of the conjugate gradient method on a vector processor
β Scribed by Hegland, Markus; Saylor, Paul E.
- Book ID
- 121421651
- Publisher
- Taylor and Francis Group
- Year
- 1992
- Tongue
- English
- Weight
- 647 KB
- Volume
- 44
- Category
- Article
- ISSN
- 0020-7160
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In this paper, we study the parallelization of the Jacobi method to solve the symmetric eigenvalue problem on a mesh of processors. To solve this problem obtaining a theoretical efficiency of 100% it is necessary to exploit the symmetry of the matrix. The only previous algorithm we know exploiting t
We consider the linear equation Ax = b where A is a sparse symmetric positive definite matrix arising from a finite element discretisation. We use the preconditioned conjugate gradient method to solve this equation, introducing an element-by-element preconditioner which is based on a Crout's decompo