Recursive Least-Squares Problems on Distributed-Memory Multiprocessors

We discuss implementations of block algorithms for recursive least squares (RLS for short) problems on ring distributed-memory multiprocessors. We consider the sliding rectangular window case which involves triangularization followed by updating and downdating of the data matrix. We compare several...

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Bibliographic Details
Published in:Journal of parallel and distributed computing 1995, Vol.24 (1), p.11-26
Main Authors: Choi, J.Y., Bojanczyk, A.W.
Format: Article
Language:English
Subjects:
Algorithmics. Computability. Computer arithmetics
Applied sciences
Computer science
control theory
systems
Computer systems and distributed systems. User interface
Exact sciences and technology
Software
Theoretical computing
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Summary:We discuss implementations of block algorithms for recursive least squares (RLS for short) problems on ring distributed-memory multiprocessors. We consider the sliding rectangular window case which involves triangularization followed by updating and downdating of the data matrix. We compare several schemes for computing the current least-squares solution, including a direct back-substitution scheme and a scheme where the previous solution vector is updated to the current solution vector by adding the so-called Kalman gain vector. The techniques are implemented on a linear array of transputers and on the Intel iPSC/2 hypercube, and evaluated with respect to their execution time and numerical accuracy.
ISSN:0743-7315
1096-0848
DOI:10.1006/jpdc.1995.1003