{"title":"小行星:可扩展的在线内存诊断","authors":"Musfiq Rahman, B. Childers","doi":"10.1145/2742854.2742861","DOIUrl":null,"url":null,"abstract":"Memory diagnostics play an important role in addressing the worsening resilience problem for DRAM main memory. As device scales reach the extremes of physical limits, memory is becoming more prone to transient and permanent errors. Online memory diagnostics can be used as part of a comprehensive strategy to mitigate errors. This paper presents a new approach, Asteroid, to incorporate memory diagnostics in a system actively serving a workload. The approach dynamically adjusts itself to workload behavior and resource availability to maximize test thoroughness and minimize performance overhead. In a 16-core enterprise server, Asteroid has modest overhead of 1% to 4% for workloads with low to high memory demand.","PeriodicalId":417279,"journal":{"name":"Proceedings of the 12th ACM International Conference on Computing Frontiers","volume":"84 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Asteroid: scalable online memory diagnostics\",\"authors\":\"Musfiq Rahman, B. Childers\",\"doi\":\"10.1145/2742854.2742861\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Memory diagnostics play an important role in addressing the worsening resilience problem for DRAM main memory. As device scales reach the extremes of physical limits, memory is becoming more prone to transient and permanent errors. Online memory diagnostics can be used as part of a comprehensive strategy to mitigate errors. This paper presents a new approach, Asteroid, to incorporate memory diagnostics in a system actively serving a workload. The approach dynamically adjusts itself to workload behavior and resource availability to maximize test thoroughness and minimize performance overhead. In a 16-core enterprise server, Asteroid has modest overhead of 1% to 4% for workloads with low to high memory demand.\",\"PeriodicalId\":417279,\"journal\":{\"name\":\"Proceedings of the 12th ACM International Conference on Computing Frontiers\",\"volume\":\"84 2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 12th ACM International Conference on Computing Frontiers\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2742854.2742861\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 12th ACM International Conference on Computing Frontiers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2742854.2742861","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Memory diagnostics play an important role in addressing the worsening resilience problem for DRAM main memory. As device scales reach the extremes of physical limits, memory is becoming more prone to transient and permanent errors. Online memory diagnostics can be used as part of a comprehensive strategy to mitigate errors. This paper presents a new approach, Asteroid, to incorporate memory diagnostics in a system actively serving a workload. The approach dynamically adjusts itself to workload behavior and resource availability to maximize test thoroughness and minimize performance overhead. In a 16-core enterprise server, Asteroid has modest overhead of 1% to 4% for workloads with low to high memory demand.
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