Block row projection method based on M-matrix splitting

We propose a hybrid sparse linear system solver based on M-matrix splitting and block-row projection (BRP). We split the sparse coefficient matrix A into two (nonsingular) M-matrices, and construct an augmented larger linear system which we solve using a BRP method. The robustness of BRP is compared with those of ILUT-preconditioned GMRES, and the sparse direct solver Pardiso. We also demonstrate the parallel scalability of BRP on a cluster of multicore nodes.