Abstract
Persistent memory gains increasing popularity in recent years. Many persistent memory systems leverage memory access monitoring to achieve user-transparent crash consistency enforcement. However, traditional program analysis-oriented memory access monitoring mechanisms incur prohibitive performance overheads in persistent memory applications. Especially, for applications developed for systems with hybrid DRAM and persistent memory, existing memory tracking approaches cannot distinguish volatile and persistent memory writes, which leads to significant unnecessary runtime cost.
This paper describes PMemTrace, a lightweight and efficient memory access monitoring approach for persistent memory. PMemTrace conducts best-effort pointer analysis to speculatively reduce as many redundant instrumentations to volatile writes as possible at compile time. Besides, PMemTrace enforces thread-local memory access permission control with the Memory Protection Keys (MPK) hardware primitive in recent Intel processors to track the mistakenly filtered persistent writes.
The evaluation results show that PMemTrace substantially outperforms the state-of-the-art memory tracking systems.
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Acknowledgment
This work is supported by National High-level Personnel for Defense Technology Program (2017-JCJQ-ZQ-013), NSF 61902405, the National University of Defense Technology Foundation under Grant Nos. ZK20-09, the Natural Science Foundation of Hunan Province of China under Grant No. 2021JJ40692 and NUDT HPCL Research Fund 202101-04. Kai Lu is the corresponding author of this paper.
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Zhang, Y., Lu, K., Wu, Z., Zhang, W. (2023). PMemTrace: Lightweight and Efficient Memory Access Monitoring for Persistent Memory. In: Meng, W., Lu, R., Min, G., Vaidya, J. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2022. Lecture Notes in Computer Science, vol 13777. Springer, Cham. https://doi.org/10.1007/978-3-031-22677-9_5
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