{"title":"Novel reconfigurable hardware implementation of polynomial matrix/vector multiplications","authors":"Server Kasap, Soydan Redif","doi":"10.1109/FPT.2014.7082785","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce a novel reconfigurable hardware architecture for computing the polynomial matrix multiplication (PMM) of polynomial matrices/vectors. The proposed algorithm exploits an extension of the fast convolution technique to multiple-input, multiple-output (MIMO) systems. The proposed architecture is the first one devoted to the hardware implementation of PMM. Hardware implementation of the algorithm is achieved via a highly pipelined, partly systolic FPGA architecture. We verify the algorithmic accuracy of the architecture, which is scalable in terms of the order of the input matrices, through FPGA-in-the-loop hardware co-simulations. Results are presented to demonstrate the accuracy and capability of the architecture.","PeriodicalId":6877,"journal":{"name":"2014 International Conference on Field-Programmable Technology (FPT)","volume":"18 1","pages":"243-247"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Field-Programmable Technology (FPT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FPT.2014.7082785","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we introduce a novel reconfigurable hardware architecture for computing the polynomial matrix multiplication (PMM) of polynomial matrices/vectors. The proposed algorithm exploits an extension of the fast convolution technique to multiple-input, multiple-output (MIMO) systems. The proposed architecture is the first one devoted to the hardware implementation of PMM. Hardware implementation of the algorithm is achieved via a highly pipelined, partly systolic FPGA architecture. We verify the algorithmic accuracy of the architecture, which is scalable in terms of the order of the input matrices, through FPGA-in-the-loop hardware co-simulations. Results are presented to demonstrate the accuracy and capability of the architecture.