May 3, 2024
Saeed Karimi

Saeed Karimi

Academic Rank: Associate professor
Address:
Degree: Ph.D in Applied Mathematics
Phone: 07733447965
Faculty: Faculty of Intelligent Systems and Data Science

Research

Title A parallel algorithm to approximate inverse factors of a matrix via sparse–sparse iterations
Type Article
Keywords
Journal APPLIED MATHEMATICS AND COMPUTATION
DOI
Researchers Saeed Karimi (First researcher)

Abstract

In [D.K. Salkuyeh, F. Toutounian, A block version algorithm to approximate inverse factors, Appl. Math. Comput., 162 (2005) 1499–1509], the authors proposed the BAIB algorithm to approximate inverse factors of a matrix. In this paper a parallel version of the BAIB algorithm is presented. In this method the BAIB algorithm is combined with computing the sparse approximate solution of a sparse linear system by sparse–sparse iterations. The new method does not require that the sparsity pattern be known in advance. Some numerical experiments on test matrices from Harwell–Boeing collection are presented to show the efficiency of the new method and comparing to the AIB algorithm.