{"title":"Optimizing energy efficiency of 3-D multicore systems with stacked DRAM under power and thermal constraints","authors":"Jie Meng, Katsutoshi Kawakami, A. Coskun","doi":"10.1145/2228360.2228477","DOIUrl":null,"url":null,"abstract":"3D multicore systems with stacked DRAM have the potential to boost system performance significantly; however, this performance increase may cause 3D systems to exceed the power budget or create thermal hot spots. This paper introduces a framework to model on-chip DRAM accesses and analyzes performance, power, and temperature tradeoffs of 3D systems. We propose a runtime optimization policy to maximize performance while maintaining power and thermal constraints. Our policy dynamically monitors workload behavior and selects among low-power and turbo operating modes accordingly. Experiments with multithreaded workloads demonstrate up to 49% energy efficiency improvements compared to existing thermal management policies.","PeriodicalId":263599,"journal":{"name":"DAC Design Automation Conference 2012","volume":"263 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"135","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"DAC Design Automation Conference 2012","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2228360.2228477","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 135
Abstract
3D multicore systems with stacked DRAM have the potential to boost system performance significantly; however, this performance increase may cause 3D systems to exceed the power budget or create thermal hot spots. This paper introduces a framework to model on-chip DRAM accesses and analyzes performance, power, and temperature tradeoffs of 3D systems. We propose a runtime optimization policy to maximize performance while maintaining power and thermal constraints. Our policy dynamically monitors workload behavior and selects among low-power and turbo operating modes accordingly. Experiments with multithreaded workloads demonstrate up to 49% energy efficiency improvements compared to existing thermal management policies.