Abstract
This paper presents the first study of building a remote-accessible persistent radix tree, named CANRT. Unlike prior works that only focus on designing single-node tree structure for non-volatile memory, we focus on optimizing remote access performance for a persistent radix tree while minimizing the persistence overhead. Simply adopting server-reply paradigm will incur heavy server CPU consumption and hence lead to high operation latency under concurrent workloads. Therefore, we design a low-latency node-oriented read mechanism and a fine-grained lock-based write mechanism to minimize the server CPU involvement in the critical path. We also devise a non-blocking resizing scheme in CANRT. The extensive experimental results on commercial Intel Optane DC Persistent Memory platform show that CANRT outperforms the state-of-art server-centric persistent radix trees by 1.19x–1.22x and 1.67x–1.72x in read and write latency, respectively. CANRT also gains improvement of 7.44x–11.15x in terms of concurrent throughput under YCSB workloads.
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Acknowledgements
This work is supported by the National Key Research and Development Program of China (No. 2018YFB1003302), SJTU-Huawei Innovation Research Lab Funding, and the China Scholarship Council (No. 201906230180).
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Ying, Y., Huang, K., Zheng, S., Tu, Y., Huang, L. (2020). CANRT: A Client-Active NVM-Based Radix Tree for Fast Remote Access. In: Qiu, M. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2020. Lecture Notes in Computer Science(), vol 12452. Springer, Cham. https://doi.org/10.1007/978-3-030-60245-1_30
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DOI: https://doi.org/10.1007/978-3-030-60245-1_30
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