{"title":"基于查找表和乘法器的浮点CORDIC旋转和矢量实现","authors":"Shen-Fu Hsiao, Chia-Shen Wen, Hsin-Mau Lee","doi":"10.1109/ISNE.2010.5669143","DOIUrl":null,"url":null,"abstract":"A unified design is presented that can execute floating-point CORDIC operations in both rotation and vectoring modes with significantly reduced computation latency. Unlike previous pipelined CORDIC implementations usually requiring a sequence of micro-rotation stages proportional to bit accuracy, the proposed design consists of only two stages, coarse and fine stages, with each stage realized using ROM, adders, and multipliers. The bit-widths of the composing hardware components are also optimized to minimize the cost while maintaining the computation accuracy. The proposed design can be applied to applications that require high-precision arithmetic operations with large data representation ranges, such as 3D graphics acceleration.","PeriodicalId":412093,"journal":{"name":"2010 International Symposium on Next Generation Electronics","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Implementation of floating-point CORDIC rotation and vectoring based on look up tables and multipliers\",\"authors\":\"Shen-Fu Hsiao, Chia-Shen Wen, Hsin-Mau Lee\",\"doi\":\"10.1109/ISNE.2010.5669143\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A unified design is presented that can execute floating-point CORDIC operations in both rotation and vectoring modes with significantly reduced computation latency. Unlike previous pipelined CORDIC implementations usually requiring a sequence of micro-rotation stages proportional to bit accuracy, the proposed design consists of only two stages, coarse and fine stages, with each stage realized using ROM, adders, and multipliers. The bit-widths of the composing hardware components are also optimized to minimize the cost while maintaining the computation accuracy. The proposed design can be applied to applications that require high-precision arithmetic operations with large data representation ranges, such as 3D graphics acceleration.\",\"PeriodicalId\":412093,\"journal\":{\"name\":\"2010 International Symposium on Next Generation Electronics\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Symposium on Next Generation Electronics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISNE.2010.5669143\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Symposium on Next Generation Electronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISNE.2010.5669143","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Implementation of floating-point CORDIC rotation and vectoring based on look up tables and multipliers
A unified design is presented that can execute floating-point CORDIC operations in both rotation and vectoring modes with significantly reduced computation latency. Unlike previous pipelined CORDIC implementations usually requiring a sequence of micro-rotation stages proportional to bit accuracy, the proposed design consists of only two stages, coarse and fine stages, with each stage realized using ROM, adders, and multipliers. The bit-widths of the composing hardware components are also optimized to minimize the cost while maintaining the computation accuracy. The proposed design can be applied to applications that require high-precision arithmetic operations with large data representation ranges, such as 3D graphics acceleration.