{"title":"LDT:用于x86系统的内存页的轻量级脏跟踪","authors":"Rohit Singh, K. P. Arun, Debadatta Mishra","doi":"10.1109/HiPC56025.2022.00023","DOIUrl":null,"url":null,"abstract":"Incremental memory checkpointing is a crucial primitive required by applications such as live migration, cloning, debugging etc. In many implementations of incremental check-pointing, the memory modifications are tracked by restricting write access to memory pages using the support provided in the memory management unit (MMU) hardware. Disabling write access impacts the performance of applications because of the page faults induced in the form of permission violation on memory store operations by the applications.In this paper, we propose LDT, a light-weight memory write monitoring mechanism to support efficient incremental check-pointing. LDT is designed to work in systems with MMU support for page dirty indicators (such as dirty-bit in x86 systems) by enabling polymorphic use of the indicators such that no other subsystem is impacted because of LDT. We design and implement LDT in the Linux kernel as an alternate to the existing write-restriction based technique. We establish the correctness and comparative efficiency of LDT through extensive experimental analysis. The results show that under write-heavy workloads, LDT outperforms write-restriction based technique by a factor of 2x in execution time. For real-world workload benchmarks such as Redis, LDT results in 2% to 8% throughput improvement compared to the state-of-the-art dirty tracking technique.","PeriodicalId":119363,"journal":{"name":"2022 IEEE 29th International Conference on High Performance Computing, Data, and Analytics (HiPC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"LDT: Lightweight Dirty Tracking of Memory Pages for x86 Systems\",\"authors\":\"Rohit Singh, K. P. Arun, Debadatta Mishra\",\"doi\":\"10.1109/HiPC56025.2022.00023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Incremental memory checkpointing is a crucial primitive required by applications such as live migration, cloning, debugging etc. In many implementations of incremental check-pointing, the memory modifications are tracked by restricting write access to memory pages using the support provided in the memory management unit (MMU) hardware. Disabling write access impacts the performance of applications because of the page faults induced in the form of permission violation on memory store operations by the applications.In this paper, we propose LDT, a light-weight memory write monitoring mechanism to support efficient incremental check-pointing. LDT is designed to work in systems with MMU support for page dirty indicators (such as dirty-bit in x86 systems) by enabling polymorphic use of the indicators such that no other subsystem is impacted because of LDT. We design and implement LDT in the Linux kernel as an alternate to the existing write-restriction based technique. We establish the correctness and comparative efficiency of LDT through extensive experimental analysis. The results show that under write-heavy workloads, LDT outperforms write-restriction based technique by a factor of 2x in execution time. For real-world workload benchmarks such as Redis, LDT results in 2% to 8% throughput improvement compared to the state-of-the-art dirty tracking technique.\",\"PeriodicalId\":119363,\"journal\":{\"name\":\"2022 IEEE 29th International Conference on High Performance Computing, Data, and Analytics (HiPC)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 29th International Conference on High Performance Computing, Data, and Analytics (HiPC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HiPC56025.2022.00023\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 29th International Conference on High Performance Computing, Data, and Analytics (HiPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HiPC56025.2022.00023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
LDT: Lightweight Dirty Tracking of Memory Pages for x86 Systems
Incremental memory checkpointing is a crucial primitive required by applications such as live migration, cloning, debugging etc. In many implementations of incremental check-pointing, the memory modifications are tracked by restricting write access to memory pages using the support provided in the memory management unit (MMU) hardware. Disabling write access impacts the performance of applications because of the page faults induced in the form of permission violation on memory store operations by the applications.In this paper, we propose LDT, a light-weight memory write monitoring mechanism to support efficient incremental check-pointing. LDT is designed to work in systems with MMU support for page dirty indicators (such as dirty-bit in x86 systems) by enabling polymorphic use of the indicators such that no other subsystem is impacted because of LDT. We design and implement LDT in the Linux kernel as an alternate to the existing write-restriction based technique. We establish the correctness and comparative efficiency of LDT through extensive experimental analysis. The results show that under write-heavy workloads, LDT outperforms write-restriction based technique by a factor of 2x in execution time. For real-world workload benchmarks such as Redis, LDT results in 2% to 8% throughput improvement compared to the state-of-the-art dirty tracking technique.