{"title":"基于自旋的神经网络的认知计算","authors":"M. Sharad, C. Augustine, G. Panagopoulos, K. Roy","doi":"10.1145/2228360.2228594","DOIUrl":null,"url":null,"abstract":"We model a step transfer function neuron with lateral spin valve (LSV) and propose its application in low power neural network hardware. The computational task in such a network is performed by nano-magnets, metal channels and programmable conductive elements, that constitute the neuron-synapse units and operate at a terminal voltage of ~20 mV. CMOS transistors provide peripheral support in the form of clocking, power gating and inter-neuron signaling. Simulations for cognitive as well as Boolean computation applications show more than 94% improvement in power consumption as compared to a conventional CMOS design at the same technology node.","PeriodicalId":263599,"journal":{"name":"DAC Design Automation Conference 2012","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Cognitive computing with spin-based neural networks\",\"authors\":\"M. Sharad, C. Augustine, G. Panagopoulos, K. Roy\",\"doi\":\"10.1145/2228360.2228594\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We model a step transfer function neuron with lateral spin valve (LSV) and propose its application in low power neural network hardware. The computational task in such a network is performed by nano-magnets, metal channels and programmable conductive elements, that constitute the neuron-synapse units and operate at a terminal voltage of ~20 mV. CMOS transistors provide peripheral support in the form of clocking, power gating and inter-neuron signaling. Simulations for cognitive as well as Boolean computation applications show more than 94% improvement in power consumption as compared to a conventional CMOS design at the same technology node.\",\"PeriodicalId\":263599,\"journal\":{\"name\":\"DAC Design Automation Conference 2012\",\"volume\":\"60 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"DAC Design Automation Conference 2012\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2228360.2228594\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"DAC Design Automation Conference 2012","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2228360.2228594","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cognitive computing with spin-based neural networks
We model a step transfer function neuron with lateral spin valve (LSV) and propose its application in low power neural network hardware. The computational task in such a network is performed by nano-magnets, metal channels and programmable conductive elements, that constitute the neuron-synapse units and operate at a terminal voltage of ~20 mV. CMOS transistors provide peripheral support in the form of clocking, power gating and inter-neuron signaling. Simulations for cognitive as well as Boolean computation applications show more than 94% improvement in power consumption as compared to a conventional CMOS design at the same technology node.