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Householder transformation for the regularized least square problem on iPSC/860

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1 Author(s)
J. Zhu ; Eng. Res. Center for Comput. Field Simulations, Mississippi State Univ., MS, USA

Discusses a householder factorization algorithm for a special type of matrix arising from the application of the Tikhnov regularization method to an ill-conditioned least square problem. The matrix involved is half dense and half sparse. The algorithm has been implemented on iPSC/860 hypercubes. By overlapping communications with computations, the code has been optimized to take advantage of the special structure of the matrix and minimize inter-node communications. Super-linear speed-up was observed in the numerical experiment for large problems. The algorithm has been used as a core routine in the program solving parameter identification problems in reservoir simulations

Published in:

Parallel Processing Symposium, 1992. Proceedings., Sixth International

Date of Conference:

23-26 Mar 1992