{"title":"Blade-OC Asynchronous Resilient Template ‡ This research has been supported in part by NSF Grant #1619415.","authors":"Moisés Herrera, Tingyu Wang, P. Beerel","doi":"10.1109/PATMOS.2018.8463998","DOIUrl":null,"url":null,"abstract":"This paper introduces a novel timing-resilient asynchronous bundled-data template called Blade-OC. The template replaces the synchronous global clock driving FFs with asynchronous controllers that drive error-detecting latches. Compared to its predecessors, the template supports a larger timing resiliency window (TRW) enabling higher performance for designs with wide variations in delay, such as seen in near and subthreshold computing. This paper quantifies this performance improvement for a variety of pipeline structures assuming lognormal datapath delay distributions.","PeriodicalId":234100,"journal":{"name":"2018 28th International Symposium on Power and Timing Modeling, Optimization and Simulation (PATMOS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 28th International Symposium on Power and Timing Modeling, Optimization and Simulation (PATMOS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PATMOS.2018.8463998","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
This paper introduces a novel timing-resilient asynchronous bundled-data template called Blade-OC. The template replaces the synchronous global clock driving FFs with asynchronous controllers that drive error-detecting latches. Compared to its predecessors, the template supports a larger timing resiliency window (TRW) enabling higher performance for designs with wide variations in delay, such as seen in near and subthreshold computing. This paper quantifies this performance improvement for a variety of pipeline structures assuming lognormal datapath delay distributions.