Alexandros-Herodotos Haritatos, G. Goumas, Nikos Anastopoulos, K. Nikas, K. Kourtis, N. Koziris
{"title":"LCA: A memory link and cache-aware co-scheduling approach for CMPs","authors":"Alexandros-Herodotos Haritatos, G. Goumas, Nikos Anastopoulos, K. Nikas, K. Kourtis, N. Koziris","doi":"10.1145/2628071.2628123","DOIUrl":null,"url":null,"abstract":"This paper presents LCA, a memory Link and Cache-Aware co-scheduling approach for CMPs. It is based on a novel application classification scheme that monitors resource utilization across the entire memory hierarchy from main memory down to CPU cores. This enables us to predict application interference accurately and support a co-scheduling algorithm that outperforms state-of-the-art scheduling policies both in terms of throughput and fairness. As LCA depends on information collected at runtime by existing monitoring mechanisms of modern processors, it can be easily incorporated in real-life co-scheduling scenarios with various application features and platform configurations.","PeriodicalId":263670,"journal":{"name":"2014 23rd International Conference on Parallel Architecture and Compilation (PACT)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 23rd International Conference on Parallel Architecture and Compilation (PACT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2628071.2628123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
This paper presents LCA, a memory Link and Cache-Aware co-scheduling approach for CMPs. It is based on a novel application classification scheme that monitors resource utilization across the entire memory hierarchy from main memory down to CPU cores. This enables us to predict application interference accurately and support a co-scheduling algorithm that outperforms state-of-the-art scheduling policies both in terms of throughput and fairness. As LCA depends on information collected at runtime by existing monitoring mechanisms of modern processors, it can be easily incorporated in real-life co-scheduling scenarios with various application features and platform configurations.