This paper describes several variants of SPCG （splitting up conjugate gradient） method suitable for parallel computing and evaluates the performance and the speed of convergence on a distributed-memory multicomputer...This paper describes several variants of SPCG （splitting up conjugate gradient） method suitable for parallel computing and evaluates the performance and the speed of convergence on a distributed-memory multicomputer. SP （splitting-up） preconditioner can be easily parallelized because other dimensions except for one dimension are independent. Among the variants, one of incomplete SPCG method, which does not carry out one of three Widiagonal matrix solvers, achieves the best performance, and this method is about 20 times faster than one-process version of the SPCG method on 32 CPU cores of the multicomputer.展开更多
文摘This paper describes several variants of SPCG （splitting up conjugate gradient） method suitable for parallel computing and evaluates the performance and the speed of convergence on a distributed-memory multicomputer. SP （splitting-up） preconditioner can be easily parallelized because other dimensions except for one dimension are independent. Among the variants, one of incomplete SPCG method, which does not carry out one of three Widiagonal matrix solvers, achieves the best performance, and this method is about 20 times faster than one-process version of the SPCG method on 32 CPU cores of the multicomputer.
