  Graphics Processing Units (GPUs) with high computational capabilities used as
modern parallel platforms to deal with complex computational problems. We use
this platform to solve large-scale linear programing problems by revised
simplex algorithm. To implement this algorithm, we propose some new memory
management strategies. In addition, to avoid cycling because of degeneracy
conditions, we use a tabu rule for entering variable selection in the revised
simplex algorithm. To evaluate this algorithm, we consider two sets of
benchmark problems and compare the speedup factors for these problems. The
comparisons demonstrate that the proposed method is highly effective and solve
the problems with the maximum speedup factors 165.2 and 65.46 with respect to
the sequential version and Matlab Linprog solver respectively.
