W. Ding, Xulong Tang, M. Kandemir, Yuanrui Zhang, Emre Kultursay
{"title":"Optimizing off-chip accesses in multicores","authors":"W. Ding, Xulong Tang, M. Kandemir, Yuanrui Zhang, Emre Kultursay","doi":"10.1145/2737924.2737989","DOIUrl":null,"url":null,"abstract":"In a network-on-chip (NoC) based manycore architecture, an off-chip data access (main memory access) needs to travel through the on-chip network, spending considerable amount of time within the chip (in addition to the memory access latency). In addition, it contends with on-chip (cache) accesses as both use the same NoC resources. In this paper, focusing on data-parallel, multithreaded applications, we propose a compiler-based off-chip data access localization strategy, which places data elements in the memory space such that an off-chip access traverses a minimum number of links (hops) to reach the memory controller that handles this access. This brings three main benefits. First, the network latency of off-chip accesses gets reduced; second, the network latency of on-chip accesses gets reduced; and finally, the memory latency of off-chip accesses improves, due to reduced queue latencies. We present an experimental evaluation of our optimization strategy using a set of 13 multithreaded application programs under both private and shared last-level caches. The results collected emphasize the importance of optimizing the off-chip data accesses.","PeriodicalId":104101,"journal":{"name":"Proceedings of the 36th ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 36th ACM SIGPLAN Conference on Programming Language Design and Implementation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2737924.2737989","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21
Abstract
In a network-on-chip (NoC) based manycore architecture, an off-chip data access (main memory access) needs to travel through the on-chip network, spending considerable amount of time within the chip (in addition to the memory access latency). In addition, it contends with on-chip (cache) accesses as both use the same NoC resources. In this paper, focusing on data-parallel, multithreaded applications, we propose a compiler-based off-chip data access localization strategy, which places data elements in the memory space such that an off-chip access traverses a minimum number of links (hops) to reach the memory controller that handles this access. This brings three main benefits. First, the network latency of off-chip accesses gets reduced; second, the network latency of on-chip accesses gets reduced; and finally, the memory latency of off-chip accesses improves, due to reduced queue latencies. We present an experimental evaluation of our optimization strategy using a set of 13 multithreaded application programs under both private and shared last-level caches. The results collected emphasize the importance of optimizing the off-chip data accesses.