A scalable 2-D parallel sparse solver
Conference
·
OSTI ID:125546
- Iowa State Univ., Ames, IA (United States)
Scalability beyond a small number of processors, typically 32 or less, is known to be a problem for existing parallel general sparse (PGS) direct solvers. This paper presents a parallel general sparse PGS direct solver for general sparse linear systems on distributed memory machines. The algorithm is based on the well-known sequential sparse algorithm Y12M. To achieve efficient parallelization, a 2-D scattered decomposition of the sparse matrix is used. The proposed algorithm is more scalable than existing parallel sparse direct solvers. Its scalability is evaluated on a 256 processor nCUBE2s machine using Boeing/Harwell benchmark matrices.
- OSTI ID:
- 125546
- Report Number(s):
- CONF-950212--
- Country of Publication:
- United States
- Language:
- English
Similar Records
A scalable parallel algorithm for sparse Cholesky factorization
A distributed-memory hierarchical solver for general sparse linear systems
SuperLU{_}DIST: A scalable distributed-memory sparse direct solver for unsymmetric linear systems
Book
·
Fri Dec 30 23:00:00 EST 1994
·
OSTI ID:87680
A distributed-memory hierarchical solver for general sparse linear systems
Journal Article
·
Tue Dec 19 23:00:00 EST 2017
· Parallel Computing
·
OSTI ID:1429626
SuperLU{_}DIST: A scalable distributed-memory sparse direct solver for unsymmetric linear systems
Journal Article
·
Tue Mar 26 23:00:00 EST 2002
· ACM Transaction on Mathematical Software
·
OSTI ID:836786