Scalable parallel algorithm for solving non-stationary systems of linear inequalities
Abstract
In this paper, a scalable iterative projection-type algorithm for solving non-stationary systems of linear inequalities is considered. A non-stationary system is understood as a large-scale system of inequalities in which coefficients and constant terms can change during the calculation process. The proposed parallel algorithm uses the concept of pseudo-projection which generalizes the notion of orthogonal projection. The parallel pseudo-projection algorithm is implemented using the parallel BSF-skeleton. An analytical estimation of the algorithm scalability boundary is obtained on the base of the BSF cost metric. The large-scale computational experiments were performed on a cluster computing system. The obtained results confirm the efficiency of the proposed approach.
Cite
@article{arxiv.2003.09956,
title = {Scalable parallel algorithm for solving non-stationary systems of linear inequalities},
author = {Leonid B. Sokolinsky and Irina M. Sokolinskaya},
journal= {arXiv preprint arXiv:2003.09956},
year = {2020}
}
Comments
This a preprint of the Work accepted for publication in Lobachevskii Journal of Mathematics, \c{opyright} 2020, Springer Nature