Parallel multifrontal solution of sparse linear least squares problems on distributed-memory multiprocessors
Conference
·
OSTI ID:125545
- Cornell Univ., Ithaca, NY (United States)
We describe the issues involved in the design and implementation of efficient parallel algorithms for solving sparse linear least squares problems on distributed-memory multiprocessors. We consider both the QR factorization method and the method of corrected semi-normal equations. The sparse QR factorization is accomplished by a parallel multifrontal scheme recently introduced. A new parallel algorithm for solving the related sparse triangular systems is proposed. Experimental results on an Intel iPSC/860 machine are described.
- OSTI ID:
- 125545
- Report Number(s):
- CONF-950212--
- Country of Publication:
- United States
- Language:
- English
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