{"title":"通过仿真方法深入了解SMR性能","authors":"Junpeng Niu, Jun Xu, Lihua Xie","doi":"10.1109/ICCA.2017.8003147","DOIUrl":null,"url":null,"abstract":"In Shingled Magnetic Recording (SMR) drives, sequential write, indirect address mapping and garbage collection (GC) are three main unique features. To plenarily utilize these properties, there are many new specific algorithms designed to improve the performance, e.g., batch write policies and active GC algorithms. To analyze those designs, a simulation model is developed to estimate the performance under different system parameters and workload properties. The simulation results thus provide plausible guidance of SMR drive design.","PeriodicalId":379025,"journal":{"name":"2017 13th IEEE International Conference on Control & Automation (ICCA)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A deep look at SMR performance via simulation approach\",\"authors\":\"Junpeng Niu, Jun Xu, Lihua Xie\",\"doi\":\"10.1109/ICCA.2017.8003147\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In Shingled Magnetic Recording (SMR) drives, sequential write, indirect address mapping and garbage collection (GC) are three main unique features. To plenarily utilize these properties, there are many new specific algorithms designed to improve the performance, e.g., batch write policies and active GC algorithms. To analyze those designs, a simulation model is developed to estimate the performance under different system parameters and workload properties. The simulation results thus provide plausible guidance of SMR drive design.\",\"PeriodicalId\":379025,\"journal\":{\"name\":\"2017 13th IEEE International Conference on Control & Automation (ICCA)\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 13th IEEE International Conference on Control & Automation (ICCA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCA.2017.8003147\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 13th IEEE International Conference on Control & Automation (ICCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCA.2017.8003147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A deep look at SMR performance via simulation approach
In Shingled Magnetic Recording (SMR) drives, sequential write, indirect address mapping and garbage collection (GC) are three main unique features. To plenarily utilize these properties, there are many new specific algorithms designed to improve the performance, e.g., batch write policies and active GC algorithms. To analyze those designs, a simulation model is developed to estimate the performance under different system parameters and workload properties. The simulation results thus provide plausible guidance of SMR drive design.