一句话：提出 MV-RLU，将 RLU 扩展为多版本同步，并通过并发自主垃圾回收提升写密集负载性能。
MV-RLU 是对 read-log-update（RLU）同步机制的扩展。RLU 具有直观编程模型和读多写少负载下的优异性能，但只维护两个版本，导致写操作较多时性能显著下降。为此，作者将 RLU 扩展为支持多版本，并提出使多版本高效的新技术。其核心是并发自主垃圾回收，避免回收不可见版本成为瓶颈，并降低版本遍历开销。评估在并发数据结构与真实应用（数据库并发控制、内存键值存储）上，与 RCU、RLU、STM、无锁方法等同步机制比较；结果表明，在不同竞争程度和数据集规模的大量负载下，MV-RLU 显著优于其他技术。
This paper presents multi-version read-log-update (MV-RLU), an extension of the read-log-update (RLU) synchronization mechanism. While RLU has many merits including an intuitive programming model and excellent performance for read-mostly workloads, we observed that the performance of RLU significantly drops in workloads with more write operations. The core problem is that RLU manages only two versions. To overcome such limitation, we extend RLU to support multi-versioning and propose new techniques to make multi-versioning efficient. At the core of MV-RLU design is concurrent autonomous garbage collection, which prevents reclaiming invisible versions being a bottleneck, and reduces the version traversal overhead the main overhead of multi-version design. We extensively evaluate MV-RLU with the state-of-the-art synchronization mechanisms, including RCU, RLU, software transactional memory (STM), and lock-free approaches, on concurrent data structures and real-world applications (database concurrency control and in-memory key-value store). Our evaluation results show that MV-RLU significantly outperforms other techniques for a wide range of workloads with varying contention levels and data-set size.
DOI 原文 ·
@inproceedings{paperbot4888,
title = {MV-RLU},
author = {Jaeho Kim and Ajit Mathew and Sanidhya Kashyap and Madhava Krishnan Ramanathan and Changwoo Min},
booktitle = {ASPLOS},
year = {2019},
doi = {10.1145/3297858.3304040}
}