论文信息 - Solution of sparse positive definite systems on a shared-memory multiprocessor

Solution of sparse positive definite systems on a shared-memory multiprocessor

Algorithms and software for solving sparse symmetric positive definite systems on serial computers have reached a high state of development. In this paper, we present algorithms for performing sparse Cholesky factorization and sparse triangular solutions on a shared-memory multiprocessor computer, along with some numerical experiments demonstrating their performance on a Sequent Balance 8000 system.

[1] H.F. Jordan,et al. Experience with pipelined multiple instruction streams , 1984, Proceedings of the IEEE.

[2] B. Buslee. Supercomputers: Value and Trends Bill Buzbee, Computer Research and Applications Group, Computing and Communications Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545 , 1987 .

[3] A. George,et al. Parallel Cholesky factorization on a shared-memory multiprocessor. Final report, 1 October 1986-30 September 1987 , 1986 .

[4] Joseph W. H. Liu,et al. Modification of the minimum-degree algorithm by multiple elimination , 1985, TOMS.

[5] Andrew Harry Sherman,et al. On the efficient solution of sparse systems of linear and nonlinear equations. , 1975 .

[6] Stanley C. Eisenstat,et al. Yale sparse matrix package I: The symmetric codes , 1982 .

[7] Joseph W. H. Liu,et al. Computational models and task scheduling for parallel sparse Cholesky factorization , 1986, Parallel Comput..

[8] Iain S. Duff,et al. Parallel implementation of multifrontal schemes , 1986, Parallel Comput..

[9] Alan George,et al. The Design of a User Interface for a Sparse Matrix Package , 1979, TOMS.

[10] J. Pasciak,et al. Computer solution of large sparse positive definite systems , 1982 .

[11] Michael T. Heath,et al. Sparse Cholesky factorization on a local-memory multiprocessor , 1988 .