Parallel Implementations of Primal and Dual Algorithms For Matrix Balancing
We report the parallel computing implementations of a primal projected gradient algorithm and the classical RAS dual algorithm for matrix balancing. The computing platform used is a network of Transputers which is suitable for coarse grained parallelization of sequential algorithms. We report computational results with dense matrices of dimension up to 315 x 315 and 100, 000 nonzero variables.
KeywordsLine Search Parallel Implementation Bipartite Network Dual Algorithm Projected Gradient Algorithm
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