A parallel implementation of the specialized interior-point algorithm for multicommodity network fows introduced in [5] is presented. In this algorithm, the positive defnite systems of each iteration are solved through a scheme that combines direct factorization and a preconditioned conjugate gradient (PCG) method. Since the solution of at least k independent linear systems is required at each iteration of the PCG, k being the number of commodities, a coarse-grained parallellization of the algorithm naturally arises, where these systems are solved on different processors. Also, several other minor steps of the algorithm are easily parallelized by commodity. An extensive set of computational results on a shared memory machine is presented, using problems of up to 2.5 million variables and 260,000 constraints. The results show that the approach is especially competitive on large, diffcult multicommodity flow problems.

A Parallel Implementation of an Interior-Point Algorithm for Multicommodity Network Flows

FRANGIONI, ANTONIO
2001-01-01

Abstract

A parallel implementation of the specialized interior-point algorithm for multicommodity network fows introduced in [5] is presented. In this algorithm, the positive defnite systems of each iteration are solved through a scheme that combines direct factorization and a preconditioned conjugate gradient (PCG) method. Since the solution of at least k independent linear systems is required at each iteration of the PCG, k being the number of commodities, a coarse-grained parallellization of the algorithm naturally arises, where these systems are solved on different processors. Also, several other minor steps of the algorithm are easily parallelized by commodity. An extensive set of computational results on a shared memory machine is presented, using problems of up to 2.5 million variables and 260,000 constraints. The results show that the approach is especially competitive on large, diffcult multicommodity flow problems.
2001
Castro, J.; Frangioni, Antonio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/175085
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