A block preconditioner for the Gl-LSMR algorithm

The global least squares minimal residual (gl-lsmr) method is an efficient solver for linear systems with multiple right-hand sides. to accelerate the convergence of the gl-lsmr method, we propose a block preconditioner for the global lsmr method which can be used for solving linear systems with a block partitioned coefficient matrix and multiple right-hand sides. numerical examples and comparing the preconditioned gl-lsmr method with the gl-lsmr method validate the effectiveness of the preconditioner. numerical results confirm that the block preconditioned gl-lsmr (bpglsmr) method has a better performance in reducing the number of iterations and cpu time