论文信息 - Scalable Parallel Sparse Factorization with Left-Right Looking Strategy on Shared Memory Multoprocessors

Scalable Parallel Sparse Factorization with Left-Right Looking Strategy on Shared Memory Multoprocessors

An efficient sparse LU factorization algorithm on popular shared memory multiprocessors is presented. Interprocess communication is critically important on these architectures—the algorithm introduces O(n) synchronization events only. No global barrier is used and a completely asynchronous scheduling scheme is one central point of the implementation. The algorithm aims at optimizing the single node performance and minimizing the communication overhead. It has been successfully tested on SUN Enterprise, DEC AlphaServer, SGI Origin 2000, Cray T90, J90, and NEC SX-4 parallel computers, delivering up to 2.3 GFlop/s on an eight processor DEC AlphaServer for medium-size semiconductor device simulations and structural engineering problems.

[1] Pontus Matstoms,et al. Parallel Sparse QR Factorization on Shared Memory Architectures , 1995, Parallel Comput..

[2] Joseph W. H. Liu. The role of elimination trees in sparse factorization , 1990 .

[3] Barry W. Peyton,et al. A Supernodal Cholesky Factorization Algorithm for Shared-Memory Multiprocessors , 1991, SIAM J. Sci. Comput..

[4] Wolfgang Fichtner,et al. Efficient Hybrid Solution of Sparse Linear Systems , 1995 .

[5] Iain S. Duff. Multiprocessing a sparse matrix code on the Alliant FX/8 , 1990 .

[6] Iain S. Duff. Multiprocessing a sparse matrix code on the Alliant FX/8 , 1989 .

[7] Edward Eric Rothberg,et al. Exploiting the memory hierarchy in sequential and parallel sparse Cholesky factorization , 1992 .

[8] Arno Liegmann. Efficient solution of large sparse linear systems , 1995 .

[9] Barry W. Peyton,et al. Progress in Sparse Matrix Methods for Large Linear Systems On Vector Supercomputers , 1987 .

[10] Wolfgang Fichtner,et al. Efficient Sparse LU Factorization with Left-Right Looking Strategy on Shared Memory Multiprocessors , 2000 .