{"title":"高效多版本快照的日志结构全局数组","authors":"H. Fujita, N. Dun, Z. Rubenstein, A. Chien","doi":"10.1109/CCGrid.2015.80","DOIUrl":null,"url":null,"abstract":"In exascale systems, increasing error rate -- particularly silent data corruption -- is a major concern. The Global ViewResilience (GVR) system builds a new model of application resilience on versioned global arrays. These arrays can be exploited for flexible, application-specific error checking and recovery. We explore a fundamental challenge to the GVR model -- the cost of versioning. We propose a novel log-structured implementation that appends new data to an update log, simultaneously tracking modified regions and versioning incrementally. We compare performance of log-structured arrays to traditional flat arrays using micro-benchmarks and three full applications, and show that versioning can be more than 10x faster, and reduce memory cost significantly. Further, in future systems with NVRAM, a log-structured approach is more tolerant onramp limitations such as write bandwidth and wear-out.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"7 3 1","pages":"281-291"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Log-Structured Global Array for Efficient Multi-Version Snapshots\",\"authors\":\"H. Fujita, N. Dun, Z. Rubenstein, A. Chien\",\"doi\":\"10.1109/CCGrid.2015.80\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In exascale systems, increasing error rate -- particularly silent data corruption -- is a major concern. The Global ViewResilience (GVR) system builds a new model of application resilience on versioned global arrays. These arrays can be exploited for flexible, application-specific error checking and recovery. We explore a fundamental challenge to the GVR model -- the cost of versioning. We propose a novel log-structured implementation that appends new data to an update log, simultaneously tracking modified regions and versioning incrementally. We compare performance of log-structured arrays to traditional flat arrays using micro-benchmarks and three full applications, and show that versioning can be more than 10x faster, and reduce memory cost significantly. Further, in future systems with NVRAM, a log-structured approach is more tolerant onramp limitations such as write bandwidth and wear-out.\",\"PeriodicalId\":6664,\"journal\":{\"name\":\"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing\",\"volume\":\"7 3 1\",\"pages\":\"281-291\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCGrid.2015.80\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGrid.2015.80","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Log-Structured Global Array for Efficient Multi-Version Snapshots
In exascale systems, increasing error rate -- particularly silent data corruption -- is a major concern. The Global ViewResilience (GVR) system builds a new model of application resilience on versioned global arrays. These arrays can be exploited for flexible, application-specific error checking and recovery. We explore a fundamental challenge to the GVR model -- the cost of versioning. We propose a novel log-structured implementation that appends new data to an update log, simultaneously tracking modified regions and versioning incrementally. We compare performance of log-structured arrays to traditional flat arrays using micro-benchmarks and three full applications, and show that versioning can be more than 10x faster, and reduce memory cost significantly. Further, in future systems with NVRAM, a log-structured approach is more tolerant onramp limitations such as write bandwidth and wear-out.