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DAC2023顶会

DRPTM: A Decoupled Read-efficient High-scalable Persistent Transactional Memory

Wenkai Liang, Hao Hu, Xiangyu Zou, Wen Xia, Yanqi Pan

2023年份
3被引次数

摘要

Persistent transactional memory (PTM) exploits transactions to provide an easy crash-consistent interface for persistent memory (PM). However, because of the substantial reader-side overhead brought on by the low bandwidth and long persistence latency of PM, present PTM research cannot scale effectively. This paper proposes a highly scalable PTM system, DRPTM, which allows nearly non-overhead reads without lowering the isolation level. DRPTM decouples persistence latency from concurrency control and traces the read-only copy maintained in logs as a lightweight read set. The evaluation shows that DRPTM significantly outperforms the state-of-the-art PTM systems for various workloads and achieves near-linear scalability.

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