{"title":"用于HECC的超线程倍增器","authors":"Gabriel Gallin, A. Tisserand","doi":"10.1109/ACSSC.2017.8335378","DOIUrl":null,"url":null,"abstract":"Modular multiplication is the most costly and common operation in hyper-elliptic curve cryptography. Over prime fields, it uses dependent partial products and reduction steps. These dependencies make FPGA implementations with fully pipelined DSP blocks difficult to optimize. We propose a new multiplier architecture with hyper-threaded capabilities. Several independent multiplications are handled in parallel for efficiently filling the pipeline and overlapping internal latencies by independent computations. It increases the silicon efficiency and leads to a better area / computation time trade-off than current state of the art. We use this hyper-threaded multiplier into small accelerators for hyper-elliptic curve cryptography in embedded systems.","PeriodicalId":296208,"journal":{"name":"2017 51st Asilomar Conference on Signals, Systems, and Computers","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Hyper-threaded multiplier for HECC\",\"authors\":\"Gabriel Gallin, A. Tisserand\",\"doi\":\"10.1109/ACSSC.2017.8335378\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Modular multiplication is the most costly and common operation in hyper-elliptic curve cryptography. Over prime fields, it uses dependent partial products and reduction steps. These dependencies make FPGA implementations with fully pipelined DSP blocks difficult to optimize. We propose a new multiplier architecture with hyper-threaded capabilities. Several independent multiplications are handled in parallel for efficiently filling the pipeline and overlapping internal latencies by independent computations. It increases the silicon efficiency and leads to a better area / computation time trade-off than current state of the art. We use this hyper-threaded multiplier into small accelerators for hyper-elliptic curve cryptography in embedded systems.\",\"PeriodicalId\":296208,\"journal\":{\"name\":\"2017 51st Asilomar Conference on Signals, Systems, and Computers\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 51st Asilomar Conference on Signals, Systems, and Computers\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACSSC.2017.8335378\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 51st Asilomar Conference on Signals, Systems, and Computers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACSSC.2017.8335378","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modular multiplication is the most costly and common operation in hyper-elliptic curve cryptography. Over prime fields, it uses dependent partial products and reduction steps. These dependencies make FPGA implementations with fully pipelined DSP blocks difficult to optimize. We propose a new multiplier architecture with hyper-threaded capabilities. Several independent multiplications are handled in parallel for efficiently filling the pipeline and overlapping internal latencies by independent computations. It increases the silicon efficiency and leads to a better area / computation time trade-off than current state of the art. We use this hyper-threaded multiplier into small accelerators for hyper-elliptic curve cryptography in embedded systems.