{"title":"Program counter based techniques for dynamic power management","authors":"C. Gniady, Y. C. Hu, Yung-Hsiang Lu","doi":"10.1109/HPCA.2004.10021","DOIUrl":null,"url":null,"abstract":"Reducing energy consumption has become one of the major challenges in designing future computing systems. We propose a novel idea of using program counters to predict I/O activities in the operating system. We present a complete design of program-counter access predictor (PCAP) that dynamically learns the access patterns of applications and predicts when an I/O device can be shut down to save energy. PCAP uses path-based correlation to observe a particular sequence of program counters leading to each idle period, and predicts future occurrences of that idle period. PCAP differs from previously proposed shutdown predictors in its ability to: (1) correlate I/O operations to particular behavior of the applications and users, (2) carry prediction information across multiple executions of the applications, and (3) attain better energy savings while incurring low mispredictions.","PeriodicalId":145009,"journal":{"name":"10th International Symposium on High Performance Computer Architecture (HPCA'04)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"53","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"10th International Symposium on High Performance Computer Architecture (HPCA'04)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCA.2004.10021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 53
Abstract
Reducing energy consumption has become one of the major challenges in designing future computing systems. We propose a novel idea of using program counters to predict I/O activities in the operating system. We present a complete design of program-counter access predictor (PCAP) that dynamically learns the access patterns of applications and predicts when an I/O device can be shut down to save energy. PCAP uses path-based correlation to observe a particular sequence of program counters leading to each idle period, and predicts future occurrences of that idle period. PCAP differs from previously proposed shutdown predictors in its ability to: (1) correlate I/O operations to particular behavior of the applications and users, (2) carry prediction information across multiple executions of the applications, and (3) attain better energy savings while incurring low mispredictions.