Matrix factorization on a hypercube multiprocessor
Conference
·
OSTI ID:5653196
This paper is concerned with parallel algorithms for matrix factorization on distributed-memory, message-passing multiprocessors, with special emphasis on the hypercube. Both Cholesky factorization of symmetric positive definite matrices and LU factorization of nonsymmetric matrices using partial pivoting are considered. The use of the resulting triangular factors to solve systems of linear equations by forward and back substitutions is also considered. Efficiencies of various parallel computational approaches are compared in terms of empirical results obtained on an Intel iPSC hypercube. 19 refs., 6 figs., 2 tabs.
- Research Organization:
- Oak Ridge National Lab., TN (USA)
- DOE Contract Number:
- AC05-84OR21400
- OSTI ID:
- 5653196
- Report Number(s):
- CONF-8508178-1; ON: DE86011775
- Country of Publication:
- United States
- Language:
- English
Similar Records
Supernodal symbolic Cholesky factorization on a local-memory multiprocessor
Efficient parallel LU factorization with pivoting on a hypercube multiprocessor
Sparse Cholesky factorization on a multiprocessor
Journal Article
·
Thu Aug 14 00:00:00 EDT 2003
· Parallel Computing
·
OSTI ID:5456424
Efficient parallel LU factorization with pivoting on a hypercube multiprocessor
Technical Report
·
Tue Oct 01 00:00:00 EDT 1985
·
OSTI ID:5001510
Sparse Cholesky factorization on a multiprocessor
Thesis/Dissertation
·
Wed Dec 31 23:00:00 EST 1986
·
OSTI ID:7183866