{"title":"Efficient FFT Implementation on a CGRA","authors":"Li Yu, Yang Jinjiang, Liu Leibo","doi":"10.1145/3395260.3395279","DOIUrl":null,"url":null,"abstract":"In this paper, we present an efficient implementation of FFT algorithm on a CGRA-based reconfigurable architecture. Radix-4 method is used in this paper according to the advantages of proposed CGRA. The performance of the radix-4 FFT implementation is optimized by the parallelism of the Processing Elements (PEs) and the multi-access scheme of the shared memory (SM). Compared with other similar reconfigurable architectures, the proposed FFT implementation on the CGRA has performance advantages. Taking 1024-point FFT as an example, we achieve 1.93X to 6.22X advantages.","PeriodicalId":103490,"journal":{"name":"Proceedings of the 2020 5th International Conference on Mathematics and Artificial Intelligence","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 5th International Conference on Mathematics and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3395260.3395279","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In this paper, we present an efficient implementation of FFT algorithm on a CGRA-based reconfigurable architecture. Radix-4 method is used in this paper according to the advantages of proposed CGRA. The performance of the radix-4 FFT implementation is optimized by the parallelism of the Processing Elements (PEs) and the multi-access scheme of the shared memory (SM). Compared with other similar reconfigurable architectures, the proposed FFT implementation on the CGRA has performance advantages. Taking 1024-point FFT as an example, we achieve 1.93X to 6.22X advantages.
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