Abstract
We propose a new preconditioned global conjugate gradient (PGL-CG) method for the solution of matrix equation AXB = C, where A and B are sparse Stieltjes matrices. The preconditioner is based on the support graph preconditioners. By using Vaidya’s maximum spanning tree precon ditioner and BFS algorithm, we present a new algorithm for computing the approximate inverse preconditioners for matrices A and B and constructing a preconditioner for the matrix equation AXB = C. This preconditioner does not require solving any linear systems and is highly parallelizable. Numerical experiments are given to show the efficiency of the new algorithm on CPU and GPU for the solution of large sparse matrix equation.
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