A scalable algorithm for solving non-stationary linear programming problems

Authors

DOI:

https://doi.org/10.26089/NumMet.v19r448

Keywords:

non-stationary high-dimension linear programming problem, NSLP algorithm, BSF parallel computation model, scalability estimation, cluster computing systems

Abstract

This paper is devoted to the scalability study of an NSLP algorithm for solving non-stationary high-dimension linear programming problems on cluster computing systems. The analysis is based on the BSF model of parallel computations. The BSF model is a new parallel computation model designed on the basis of BSP and SPMD models. The brief descriptions of the NSLP algorithm and the BSF model are given. The NSLP algorithm implementation in the form of a BSF program is considered. On the basis of the BSF cost metric, the upper bound of the NSLP algorithm scalability is derived and its parallel efficiency is estimated. The NSLP algorithm implementation using BSF skeleton is described. The scalability estimates obtained analytically and experimentally are compared.

Author Biographies

I.M. Sokolinskaya

South Ural State University
• Associate Professor

L.B. Sokolinsky

South Ural State University
• Vice-Rector for Informatization

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Published

24-12-2018

How to Cite

Соколинская И.М., Соколинский Л.Б. A Scalable Algorithm for Solving Non-Stationary Linear Programming Problems // Numerical Methods and Programming (Vychislitel’nye Metody i Programmirovanie). 2018. 19. 540-550. doi 10.26089/NumMet.v19r448

Issue

Section

Section 1. Numerical methods and applications

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