An FPGA implementation of the simplex algorithm

Samuel Bayliss, C. Bouganis, G. Constantinides, W. Luk
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引用次数: 32

Abstract

Linear programming is applied to a large variety of scientific computing applications and industrial optimization problems. The Simplex algorithm is widely used for solving linear programs due to its robustness and scalability properties. However, application of the current software implementations of the Simplex algorithm to real-life optimization problems are time consuming when used as the bounding engine within an integer linear programming framework. This work aims to accelerate the Simplex algorithm by proposing a novel parameterizable hardware implementation of the algorithm on an FPGA. Evaluation of the proposed design using real problems demonstrates a speedup of up to 20 times over a highly optimized commercial software implementation running on a 3.4GHz Pentium 4 processor, which is itself 100 times faster than one of the main public domain solvers
单纯形算法的FPGA实现
线性规划被广泛应用于各种科学计算应用和工业优化问题。单纯形算法因其鲁棒性和可扩展性被广泛应用于求解线性规划。然而,将Simplex算法的当前软件实现应用于实际优化问题时,在整数线性规划框架内用作边界引擎是非常耗时的。这项工作旨在通过在FPGA上提出一种新的可参数化的算法硬件实现来加速单纯形算法。使用实际问题对提出的设计进行的评估表明,与运行在3.4GHz Pentium 4处理器上的高度优化的商业软件实现相比,该设计的速度提高了20倍,而Pentium 4处理器本身比主要的公共领域解决方案快100倍
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