ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2022, Vol. 59 ›› Issue (3): 553-567.doi: 10.7544/issn1000-1239.20210541

所属专题: 2022存储系统与智能处理专题

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  1. (武汉理工大学计算机科学与技术学院 武汉 430073) (
  • 出版日期: 2022-03-07
  • 基金资助: 

Endurance Aware Out-of-Place Update for Persistent Memory

Cai Changxing, Du Yajuan, Zhou Taiyu   

  1. (School of Computer Science and Technology, Wuhan University of Technology, Wuhan 430073)
  • Online: 2022-03-07
  • Supported by: 
    This work was supported by the National Natural Science Foundation of China (61802287) and the State Key Laboratory of Computer Architecture (ICT,CAS) (CARCH201903).

摘要: 持久性内存具有非易失性、可字节寻址、随机读写速度快、能耗低以及可扩展性强等优良特性,为大数据存储和处理提供了新的机遇.然而,持久性内存系统的故障一致性问题为其广泛推广应用带来挑战.现有一致性保证的研究工作通常以增加额外读写为代价,对持久性内存系统的性能和寿命在时间和空间维度产生了一定的影响.为了降低该影响,提出一种耐久性感知的持久性内存异地更新机制(endurance aware out-of-place update for persistent memory, EAOOP).通过软件透明的异地更新技术,为持久性内存提供耐久性感知的内存管理,将数据交替刷新至原始数据区域和更新数据区域.EAOOP既保证了系统的故障一致性,又避免了冗余的数据合并操作.同时,为了高效利用内存空间,在后台执行轻量级垃圾回收,处理更新数据区域的旧数据,减少了额外的写放大和带宽占用,从而进一步降低了对持久性内存寿命和性能的影响.实验显示,EAOOP相比于现有工作,具有更高的性能和更少的开销.其中,事务处理吞吐量提升了1.6倍,总线延迟和写数量分别减少了27.3%和32.4%.

关键词: 持久性内存, 故障一致性, 异地更新, 持久化, 垃圾回收

Abstract: Persistent memory has excellent characteristics such as non-volatility, byte-addressable, fast random read and write speed, low energy consumption, and large scalability, which provides new opportunities for big data storage and processing. However, the problem of crash consistency of persistent memory systems poses challenges to its widespread application. Existing research work on crash consistency guarantee usually takes extra read and write as the cost, which has a certain impact on the performance and lifetime of persistent memory systems in the time and space dimensions. To reduce this impact, an endurance aware out-of-place update for persistent memory(EAOOP) is proposed. Through software transparent out-of-place update technology, endurance aware memory management is provided for persistent memory, and data is alternately refreshed to the original data region and the updated data region. EAOOP not only guarantees the system’s crash consistency but also avoids redundant data merging operations. At the same time, to efficiently use the memory space, a lightweight garbage collection is performed in the background to process the old data in the updated data region, reducing extra write amplification and bandwidth occupation, thereby further reducing the impact on the lifetime and performance of the persistent memory. Evaluations show that EAOOP has higher performance and less overhead compared with existing work. Among them, the transaction throughput is increased by 1.6 times, and the critical path latency and the write number are decreased by 1.3 times.

Key words: persistent memory, crash consistency, out-of-place update, persistence, garbage collection