On the performance of parallel approximate inverse preconditioning using Java multithreading techniques

In this paper a parallel shared memory Java multithreaded design and implementation of the explicit approximate inverse preconditioning is presented for solving efficiently arrow-type linear systems on symmetric multiprocessor systems. A new parallel algorithm for computing a class of optimized approximate inverse matrix is introduced. The performance on a symmetric multiprocessor system, using Java multithreading, is investigated by solving characteristic arrow-type linear systems and numerical results are given, considering the parallel performance of the construction of the optimized approximate inverse and the explicit preconditioned generalized conjugate gradient square scheme.