SmartMD: A High Performance Deduplication Engine with Mixed Pages

Authors: 

Fan Guo, University of Science and Technology of China; Yongkun Li, University of Science and Technology of China; Collaborative Innovation Center of High Performance Computing, NUDT; Yinlong Xu, University of Science and Technology of China; Anhui Province Key Laboratory of High Performance Computing, USTC; Song Jiang, University of Texas, Arlington; John C. S. Lui, The Chinese University of Hong Kong

Abstract: 

In hypervisor-based virtualization environments, translation lookaside buffers (TLBs) misses may induce two-dimensional page table walks, which may incur a long access latency, and this issue becomes worse with ever increasing memory capacity. To reduce the overhead of TLB misses, large pages (e.g., 2M-pages) are widely supported in modern hardware platforms to reduce the number of page table entries. However, memory management with large pages can be inefficient in deduplication, leading to low utilization of memory, which is a precious resource for a variety of applications.

To simultaneously enjoy benefits of high performance by accessing memory with large pages (e.g., 2M-pages) and high deduplication rate by managing memory with base pages (e.g., 4K-pages), we propose Smart Memory Deduplciation, or SmartMD in short, which is an adaptive and efficient management scheme for mixed-page memory. Specifically, we propose two lightweight schemes to accurately monitor pages’ access frequency and repetition rate, and present a dynamic and adaptive conversion scheme to selectively split or reconstruct large pages. We implement a prototype system and conduct extensive experiments with various workloads. Experiment results show that SmartMD can simultaneously achieve high access performance similar to systems using large pages, and achieves a deduplication rate similar to that applying aggressive deduplication scheme (i.e., KSM) at the same time on base pages.

Open Access Media

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.

BibTeX
@inproceedings {203179,
author = {Fan Guo and Yongkun Li and Yinlong Xu and Song Jiang and John C. S. Lui},
title = {SmartMD: A High Performance Deduplication Engine with Mixed Pages},
booktitle = {2017 {USENIX} Annual Technical Conference ({USENIX} {ATC} 17)},
year = {2017},
isbn = {978-1-931971-38-6},
address = {Santa Clara, CA},
pages = {733--744},
url = {https://www.usenix.org/conference/atc17/technical-sessions/presentation/guo-fan},
publisher = {{USENIX} Association},
month = jul,
}

Presentation Audio