SAC: rethinking the cache replacement policy for SSD-based storage systems

  • Authors:

  • Zhiguang Chen;Nong Xiao;Fang Liu

  • Affiliations:

  • National University of Defense Technology;National University of Defense Technology;National University of Defense Technology

  • Venue:
  • Proceedings of the 5th Annual International Systems and Storage Conference
  • Year:
  • 2012

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Abstract

Solid-state drives (SSDs) are widely used in storage systems. However, algorithms adopted by existing operating systems generally consider the underlying devices as hard disks, and thus are rarely optimized for SSDs. In this paper, we focus on a classical research issue, the cache replacement policy, and design a new policy by taking the parallelism of SSDs into account. A typical SSD contains several parallel channels. Some channels contain more hot data, thus are busy with read requests. The other channels may only contain cold data. So, workloads among these channels may be unbalanced. Requests issued to busy channels may take a while to address, whereas requests issued to idle channels may be served rapidly. We design a new cache replacement policy for read data, which considers the unbalanced workloads among channels. The policy gives higher priority to evicting pages from idle channels because they are more easily retrieved. On the other hand, pages from busy channels are protected. In this manner, the average latency for obtaining pages is reduced. However, SSDs are black boxes, with operating systems are blind to the channel from which a page comes. Therefore, we propose a simple scheme that determines whether a page is from a busy or an idle channel. The scheme monitor the page requests issued to the underlying storage device. When a page request is returned, and many page requests issued earlier than it have not been returned, the page is assumed to be from an idle channel. We compare our cache replacement policy with others via trace-driven simulations. The performance is measured in terms of average response time. Comparison candidates include LRU, ARC and the policy adopted by Linux. The experimental results show that our policy outperforms the other policies on most traces when workloads among channels are unbalanced.