{"title":"Enabling software management for multicore caches with a lightweight hardware support","authors":"Jiang Lin, Q. Lu, Xiaoning Ding, Zhao Zhang, Xiaodong Zhang, P. Sadayappan","doi":"10.1145/1654059.1654074","DOIUrl":null,"url":null,"abstract":"The management of shared caches in multicore processors is a critical and challenging task. Many hardware and OS-based methods have been proposed. However, they may be hardly adopted in practice due to their non-trivial overheads, high complexities, and/or limited abilities to handle increasingly complicated scenarios of cache contention caused by many-cores. In order to turn cache partitioning methods into reality in the management of multicore processors, we propose to provide an affordable and lightweight hardware support to coordinate with OS-based cache management policies. The proposed methods are scalable to many-cores, and perform comparably with other proposed hardware solutions, but have much lower overheads, therefore can be easily adopted in commodity processors. Having conducted extensive experiments with 37 multi-programming workloads, we show the effectiveness and scalability of the proposed methods. For example on 8-core systems, one of our proposed policies improves performance over LRU-based hardware cache management by 14.5% on average.","PeriodicalId":371415,"journal":{"name":"Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis","volume":"236 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"44","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1654059.1654074","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 44
Abstract
The management of shared caches in multicore processors is a critical and challenging task. Many hardware and OS-based methods have been proposed. However, they may be hardly adopted in practice due to their non-trivial overheads, high complexities, and/or limited abilities to handle increasingly complicated scenarios of cache contention caused by many-cores. In order to turn cache partitioning methods into reality in the management of multicore processors, we propose to provide an affordable and lightweight hardware support to coordinate with OS-based cache management policies. The proposed methods are scalable to many-cores, and perform comparably with other proposed hardware solutions, but have much lower overheads, therefore can be easily adopted in commodity processors. Having conducted extensive experiments with 37 multi-programming workloads, we show the effectiveness and scalability of the proposed methods. For example on 8-core systems, one of our proposed policies improves performance over LRU-based hardware cache management by 14.5% on average.