Distributed orthogonal factorization

Authors:
A. Pothen;P. Raghavan
Affiliations:
Computer Science Department, Whitmore Lab, The Pennsylvania State University, University Park, PA;Computer Science Department, Whitmore Lab, The Pennsylvania State University, University Park, PA
Venue:
C3P Proceedings of the third conference on Hypercube concurrent computers and applications - Volume 2
Year:
1989

Citing 2
Cited 3

A data structure for sparse QR and LU factorizations

SIAM Journal on Scientific and Statistical Computing - Telecommunication Programs at U.S. Universities
On Stable Parallel Linear System Solvers

Journal of the ACM (JACM)

What have we learnt from using real parallel machines to solve real problems?

C3P Proceedings of the third conference on Hypercube concurrent computers and applications - Volume 2
Parallel unit tangent vector computation for homotopy curve tracking on a hypercube

CSC '90 Proceedings of the 1990 ACM annual conference on Cooperation
Note on unit tangent vector computation for homotopy curve tracking on a hypercube

Parallel Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

We describe several algorithms for computing the orthogonal factorization on distributed memory multiprocessors. One of the algorithms is based on Givens rotations, two others employ column Householder transformations but with different communication schemes: broadcast and pipelined ring. A fourth algorithm is a hybrid; it uses Househlolder transformations and Givens rotations in separate phases. We present expressions for the arithmetic and communication complexity of each algorithm. The algorithms were implemented on an iPSC-286 and the observed times agree well with our analyses.