{"title":"一种低功耗rns增强型算术单元的设计","authors":"Piotr Patronik, S. Piestrak","doi":"10.1109/LASCAS.2016.7451032","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new approach to use Residue Number System (RNS) to design an arithmetic coprocessing unit, which allows to parallelize execution of addition and multiplication. The chosen RNS is a 5-moduli set composed of a larger even modulus 213 and four moduli of the type 2n - 1, which all fit into the 32-bit word of the processor. The RNS operations are implemented in hardware, except for the reverse conversion which is implemented in software. Simulation experiments performed on synthesized five-operation arithmetic unit show that at a small hardware and software cost can be achieved 10% energy saving for a constant-coefficient filter application and up to 25% for the matrix multiplication, compared to executions using a positional arithmetic unit.","PeriodicalId":129875,"journal":{"name":"2016 IEEE 7th Latin American Symposium on Circuits & Systems (LASCAS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Design of a low-power RNS-enhanced arithmetic unit\",\"authors\":\"Piotr Patronik, S. Piestrak\",\"doi\":\"10.1109/LASCAS.2016.7451032\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a new approach to use Residue Number System (RNS) to design an arithmetic coprocessing unit, which allows to parallelize execution of addition and multiplication. The chosen RNS is a 5-moduli set composed of a larger even modulus 213 and four moduli of the type 2n - 1, which all fit into the 32-bit word of the processor. The RNS operations are implemented in hardware, except for the reverse conversion which is implemented in software. Simulation experiments performed on synthesized five-operation arithmetic unit show that at a small hardware and software cost can be achieved 10% energy saving for a constant-coefficient filter application and up to 25% for the matrix multiplication, compared to executions using a positional arithmetic unit.\",\"PeriodicalId\":129875,\"journal\":{\"name\":\"2016 IEEE 7th Latin American Symposium on Circuits & Systems (LASCAS)\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-04-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 7th Latin American Symposium on Circuits & Systems (LASCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/LASCAS.2016.7451032\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 7th Latin American Symposium on Circuits & Systems (LASCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LASCAS.2016.7451032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design of a low-power RNS-enhanced arithmetic unit
In this paper, we propose a new approach to use Residue Number System (RNS) to design an arithmetic coprocessing unit, which allows to parallelize execution of addition and multiplication. The chosen RNS is a 5-moduli set composed of a larger even modulus 213 and four moduli of the type 2n - 1, which all fit into the 32-bit word of the processor. The RNS operations are implemented in hardware, except for the reverse conversion which is implemented in software. Simulation experiments performed on synthesized five-operation arithmetic unit show that at a small hardware and software cost can be achieved 10% energy saving for a constant-coefficient filter application and up to 25% for the matrix multiplication, compared to executions using a positional arithmetic unit.