{"title":"Bandwidth Allocation in Silicon-Photonic Networks Using Application Instrumentation","authors":"A. Narayan, A. Joshi, A. Coskun","doi":"10.1109/HPEC43674.2020.9286151","DOIUrl":null,"url":null,"abstract":"Photonic network-on-chips, despite their low-latency and high-bandwidth-density advantages in large manycore systems, suffer from high power overhead. This overhead is further exacerbated by the high bandwidth demands of data-centric applications. Prior works utilize bandwidth allocation policies at system-level to minimize photonic power and provide required bandwidth for applications. We present an approach to minimize the bandwidth requirements by instrumenting an application at the software level. This instrumented information is used to assist bandwidth allocation at system-level, thereby reducing the photonic power. We instrument PageRank application and demonstrate 35% lower power using instrumentation-assisted bandwidth allocation on PageRank running real-world graphs compared to bandwidth allocation on uninstrumented PageRank.","PeriodicalId":168544,"journal":{"name":"2020 IEEE High Performance Extreme Computing Conference (HPEC)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE High Performance Extreme Computing Conference (HPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPEC43674.2020.9286151","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
Photonic network-on-chips, despite their low-latency and high-bandwidth-density advantages in large manycore systems, suffer from high power overhead. This overhead is further exacerbated by the high bandwidth demands of data-centric applications. Prior works utilize bandwidth allocation policies at system-level to minimize photonic power and provide required bandwidth for applications. We present an approach to minimize the bandwidth requirements by instrumenting an application at the software level. This instrumented information is used to assist bandwidth allocation at system-level, thereby reducing the photonic power. We instrument PageRank application and demonstrate 35% lower power using instrumentation-assisted bandwidth allocation on PageRank running real-world graphs compared to bandwidth allocation on uninstrumented PageRank.