Using Chebyshev polynomials and approximate inverse triangular factorizations for preconditioning the conjugate gradient method

DOI10.1134/S0965542512020091zbMath1245.65035WikidataQ114075120 ScholiaQ114075120MaRDI QIDQ2901137

Igor E. Kaporin

Publication date: 16 July 2012

Published in: Computational Mathematics and Mathematical Physics (Search for Journal in Brave)

zbMATH Keywords

Chebyshev polynomialsnumerical examplesparallel computationcondition numberconjugate gradient methodsparse matrixpolynomial preconditioningsymmetric positive definite matrixsparse matrix-vector productsapproximate inverse triangular factorizations

Mathematics Subject Classification ID

Computational methods for sparse matrices (65F50) Factorization of matrices (15A23) Positive matrices and their generalizations; cones of matrices (15B48) Parallel numerical computation (65Y05) Preconditioners for iterative methods (65F08)

Related Items (3)

Combination of numerical and structured approaches to the construction of a second-order incomplete triangular factorization in parallel preconditioning methods ⋮ Parallel matrix-free polynomial preconditioners with application to flow simulations in discrete fracture networks ⋮ Some ways of parallel implementation of the conjugate gradient method with an implicit factorized preconditioner

Uses Software

• SparseMatrix
• ParaSails

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