{"title":"新颖的可重构多项式矩阵/矢量乘法的硬件实现","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":"{\"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}","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}
Novel reconfigurable hardware implementation of polynomial matrix/vector multiplications
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.