Jinrui Cao, Om Rameshwar Gatla, Mai Zheng, Dong Dai, Vidya Eswarappa, Yan Mu, Yong Chen
{"title":"PFault","authors":"Jinrui Cao, Om Rameshwar Gatla, Mai Zheng, Dong Dai, Vidya Eswarappa, Yan Mu, Yong Chen","doi":"10.1145/3205289.3205302","DOIUrl":null,"url":null,"abstract":"High-performance parallel file systems (PFSes) are of prime importance today. However, despite the importance, their reliability is much less studied compared with that of local storage systems, largely due to the lack of an effective analysis methodology. In this paper, we introduce PFault, a general framework for analyzing the failure handling of PFSes. PFault automatically emulates the failure state of each storage device in the target PFS based on a set of well-defined fault models, and enables analyzing the recoverability of the PFS under faults systematically. To demonstrate the practicality, we apply PFault to study Lustre, one of the most widely used PFSes. Our analysis reveals a number of cases where Lustre's checking and repairing utility LFSCK fails with unexpected symptoms (e.g., I/O error, hang, reboot). Moreover, with the help of PFault, we are able to identify a resource leak problem where a portion of Lustre's internal namespace and storage space become unusable even after running LFSCK. On the other hand, we also verify that the latest Lustre has made noticeable improvement in terms of failure handling comparing to a previous version. We hope our study and framework can help improve PFSes for reliable high-performance computing.","PeriodicalId":441217,"journal":{"name":"Proceedings of the 2018 International Conference on Supercomputing","volume":"115 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"PFault\",\"authors\":\"Jinrui Cao, Om Rameshwar Gatla, Mai Zheng, Dong Dai, Vidya Eswarappa, Yan Mu, Yong Chen\",\"doi\":\"10.1145/3205289.3205302\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"High-performance parallel file systems (PFSes) are of prime importance today. However, despite the importance, their reliability is much less studied compared with that of local storage systems, largely due to the lack of an effective analysis methodology. In this paper, we introduce PFault, a general framework for analyzing the failure handling of PFSes. PFault automatically emulates the failure state of each storage device in the target PFS based on a set of well-defined fault models, and enables analyzing the recoverability of the PFS under faults systematically. To demonstrate the practicality, we apply PFault to study Lustre, one of the most widely used PFSes. Our analysis reveals a number of cases where Lustre's checking and repairing utility LFSCK fails with unexpected symptoms (e.g., I/O error, hang, reboot). Moreover, with the help of PFault, we are able to identify a resource leak problem where a portion of Lustre's internal namespace and storage space become unusable even after running LFSCK. On the other hand, we also verify that the latest Lustre has made noticeable improvement in terms of failure handling comparing to a previous version. We hope our study and framework can help improve PFSes for reliable high-performance computing.\",\"PeriodicalId\":441217,\"journal\":{\"name\":\"Proceedings of the 2018 International Conference on Supercomputing\",\"volume\":\"115 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2018 International Conference on Supercomputing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3205289.3205302\",\"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 2018 International Conference on Supercomputing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3205289.3205302","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
High-performance parallel file systems (PFSes) are of prime importance today. However, despite the importance, their reliability is much less studied compared with that of local storage systems, largely due to the lack of an effective analysis methodology. In this paper, we introduce PFault, a general framework for analyzing the failure handling of PFSes. PFault automatically emulates the failure state of each storage device in the target PFS based on a set of well-defined fault models, and enables analyzing the recoverability of the PFS under faults systematically. To demonstrate the practicality, we apply PFault to study Lustre, one of the most widely used PFSes. Our analysis reveals a number of cases where Lustre's checking and repairing utility LFSCK fails with unexpected symptoms (e.g., I/O error, hang, reboot). Moreover, with the help of PFault, we are able to identify a resource leak problem where a portion of Lustre's internal namespace and storage space become unusable even after running LFSCK. On the other hand, we also verify that the latest Lustre has made noticeable improvement in terms of failure handling comparing to a previous version. We hope our study and framework can help improve PFSes for reliable high-performance computing.