{"title":"ISSCC 2019 Session 14 Overview: Machine Learning and Digital LDO Circuits","authors":"Digital Circuits Subcommittee","doi":"10.1109/isscc.2019.8662347","DOIUrl":null,"url":null,"abstract":"In this session, seven papers highlight developments in machine learning and digital low-dropout (LDO) linear regulators. The papers demonstrate a hybrid digital and mixed-signal computing platform for swarm robotics, bi-directional memory delay lines to perform time-domain MAC operations, hybrid in-/near-memory compute SRAM and resistive RAM for/with resilience techniques. The digital LDO papers present a computational regulation scheme, a sub-nA wide-dynamic-range implementation and a universal modular hybrid LDO in 14nm CMOS. Session Chair: Vivek De Intel, Beaverton, OR Associate Chair: Ping-Ying Wang CMOS-Crystal Technology, Zhubei City, Hsinchu County, Taiwan","PeriodicalId":265551,"journal":{"name":"2019 IEEE International Solid- State Circuits Conference - (ISSCC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Solid- State Circuits Conference - (ISSCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/isscc.2019.8662347","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this session, seven papers highlight developments in machine learning and digital low-dropout (LDO) linear regulators. The papers demonstrate a hybrid digital and mixed-signal computing platform for swarm robotics, bi-directional memory delay lines to perform time-domain MAC operations, hybrid in-/near-memory compute SRAM and resistive RAM for/with resilience techniques. The digital LDO papers present a computational regulation scheme, a sub-nA wide-dynamic-range implementation and a universal modular hybrid LDO in 14nm CMOS. Session Chair: Vivek De Intel, Beaverton, OR Associate Chair: Ping-Ying Wang CMOS-Crystal Technology, Zhubei City, Hsinchu County, Taiwan
在本次会议上，七篇论文重点介绍了机器学习和数字低差(LDO)线性稳压器的发展。论文展示了用于群体机器人的混合数字和混合信号计算平台，用于执行时域MAC操作的双向存储器延迟线，用于/具有弹性技术的混合内/近存储器计算SRAM和电阻性RAM。数字LDO论文提出了一个计算调节方案，一个亚na宽动态范围实现和一个通用模块化混合LDO在14nm CMOS。会议主席:Vivek De Intel, Beaverton, OR副主席:Wang Ping-Ying - crystal Technology, Zhubei City, sinchu County, Taiwan
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