Samuel Bayliss, C. Bouganis, G. Constantinides, W. Luk
{"title":"An FPGA implementation of the simplex algorithm","authors":"Samuel Bayliss, C. Bouganis, G. Constantinides, W. Luk","doi":"10.1109/FPT.2006.270294","DOIUrl":null,"url":null,"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","PeriodicalId":354940,"journal":{"name":"2006 IEEE International Conference on Field Programmable Technology","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE International Conference on Field Programmable Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FPT.2006.270294","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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