Title

Solving Equality Constrained Least Squares Problems

Abstract

Constrained least squares problems occur often in practice, mostly as sub-problems in many optimization contexts. For solving large and sparse instances of these problems on parallel architectures with distributed memory, the use of static data structures to represent the sparse matrix is preferred during the factorization. But the accurate detection of the rank of the constraint matrix is also very critical to the accuracy of the computed solution. In this work, we examine the solution of the constrained problem using weighting approach. We demonstrate that all computations can be carried out using a static data structure that is generated using the symbolic structure of the input matrices, making use of a recently proposed rank detection procedure. We show good speed-ups in solving large and sparse equality conditioned least squares problems on hypercubes up to 128 processors.

Publication Date

12-1-1992

Publication Title

Proccedings of the Scalable High Performance Computing Conference-SHPCC-92

Number of Pages

381-384

Document Type

Article; Proceedings Paper

Identifier

scopus

Personal Identifier

scopus

Socpus ID

0026963611 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0026963611

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