Pisces: A Scalable and Efficient Persistent Transactional Memory


Jinyu Gu, Qianqian Yu, Xiayang Wang, Zhaoguo Wang, Binyu Zang, Haibing Guan, and Haibo Chen, Shanghai Jiao Tong University


Persistent transactional memory (PTM) programming model has recently been exploited to provide crash-consistent transactional interfaces to ease programming atop NVM. However, existing PTM designs either incur high reader-side overhead due to blocking or long delay in the writer side (efficiency), or place excessive constraints on persistent ordering (scalability). This paper presents Pisces, a read-friendly PTM that exploits snapshot isolation (SI) on NVM. The key design of Pisces is based on two observations: the redo logs of transactions can be reused as newer versions for the data, and an intuitive MVCC-based design has read deficiency. Based on the observations, we propose a dual-version concurrency control (DVCC) protocol that maintains up to two versions in NVM-backed storage hierarchy. Together with a three-stage commit protocol, Pisces ensures SI and allows more transactions to commit and persist simultaneously. Most importantly, it promises a desired feature: hiding NVM persistence overhead from reads and allowing nearly non-blocking reads. Experimental evaluation on an Intel 40-thread (20-core) machine with real NVM equipped shows that Pisces outperforms the state-of-the-art design (i.e., DUDETM) by up to 6.3× for micro-benchmarks and 4.6× for TPC-C new order transaction, and also scales much better. The persistency cost is from 19% to 50% for 40 threads.

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@inproceedings {234896,
author = {Jinyu Gu and Qianqian Yu and Xiayang Wang and Zhaoguo Wang and Binyu Zang and Haibing Guan and Haibo Chen},
title = {Pisces: A Scalable and Efficient Persistent Transactional Memory},
booktitle = {2019 USENIX Annual Technical Conference (USENIX ATC 19)},
year = {2019},
isbn = {978-1-939133-03-8},
address = {Renton, WA},
pages = {913--928},
url = {http://www.usenix.org/conference/atc19/presentation/gu},
publisher = {USENIX Association},
month = jul

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