{"title":"Featherlight on-the-fly false-sharing detection","authors":"Milind Chabbi, Shasha Wen, Xu Liu","doi":"10.1145/3178487.3178499","DOIUrl":null,"url":null,"abstract":"Shared-memory parallel programs routinely suffer from false sharing---a performance degradation caused by different threads accessing different variables that reside on the same CPU cacheline and at least one variable is modified. State-of-the-art tools detect false sharing via a heavyweight process of logging memory accesses and feeding the ensuing access traces to an offline cache simulator. We have developed Feather, a lightweight, on-the-fly false-sharing detection tool. Feather achieves low overhead by exploiting two hardware features ubiquitous in commodity CPUs: the performance monitoring units (PMU) and debug registers. Additionally, Feather is a first-of-its-kind tool to detect false sharing in multi-process applications that use shared memory. Feather allowed us to scale false-sharing detection to myriad codes. Feather detected several false-sharing cases in important multi-core and multi-process codes including previous PPoPP artifacts. Eliminating false sharing resulted in dramatic (up to 16x) speedups.","PeriodicalId":193776,"journal":{"name":"Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3178487.3178499","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
Shared-memory parallel programs routinely suffer from false sharing---a performance degradation caused by different threads accessing different variables that reside on the same CPU cacheline and at least one variable is modified. State-of-the-art tools detect false sharing via a heavyweight process of logging memory accesses and feeding the ensuing access traces to an offline cache simulator. We have developed Feather, a lightweight, on-the-fly false-sharing detection tool. Feather achieves low overhead by exploiting two hardware features ubiquitous in commodity CPUs: the performance monitoring units (PMU) and debug registers. Additionally, Feather is a first-of-its-kind tool to detect false sharing in multi-process applications that use shared memory. Feather allowed us to scale false-sharing detection to myriad codes. Feather detected several false-sharing cases in important multi-core and multi-process codes including previous PPoPP artifacts. Eliminating false sharing resulted in dramatic (up to 16x) speedups.