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A high-performance and endurable SSD cache for parity-based RAID

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Abstract

Solid-state drives (SSDs) have been widely used as caching tier for disk-based RAID systems to speed up data-intensive applications. However, traditional cache schemes fail to effectively boost the parity-based RAID storage systems (e.g., RAID-5/6), which have poor random write performance due to the small-write problem. What’s worse, intensive cache writes can wear out the SSD quickly, which causes performance degradation and cost increment. In this article, we present the design and implementation of KDD, an efficient SSD-based caching system which Keeps Data and Deltas in SSD. When write requests hit in the cache, KDD dispatches the data to the RAID storage without updating the parity blocks to mitigate the small write penalty, and compactly stores the compressed deltas in SSD to reduce the cache write traffic while guaranteeing reliability in case of disk failures. In addition, KDD organizes the metadata partition on SSD as a circular log to make the cache persistent with low overhead. We evaluate the performance of KDD via both simulations and prototype implementations. Experimental results show that KDD effectively reduces the small write penalty while extending the lifetime of the SSD-based cache by up to 6.85 times.

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Acknowledgements

This work was supported by the National High Technology Research and Development Program (863 Program) (2015AA015301), and the National Natural Science Foundation of China (Grant Nos. 61472153, 61502191). The preliminary conference version appears in the Proceedings of the 45th International Conference on Parallel Processing (ICPP), 2016.

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Authors and Affiliations

  1. Wuhan National Lab for Optoelectronics, Key Laboratory of Information Storage System, (School of Computer Science and Technology, Huazhong University of Science and Technology), Ministry of Education of China, Wuhan, 430074, China

    Chu Li, Dan Feng, Yu Hua & Fang Wang

Authors
  1. Chu Li
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  2. Dan Feng
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  4. Fang Wang
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Corresponding author

Correspondence to Dan Feng.

Additional information

Chu Li received his BE degree in computer science and technology and the PhD degree in computer architecture from the Huazhong University of Science and Technology, China. His current research interests include file system, RAID storage system, and NAND flash memory, etc.

Dan Feng received the BE, ME, and the PhD degrees in computer science and technology in 1991, 1994, and 1997, respectively, from the Huazhong University of Science and Technology (HUST), China. She is a professor and vice dean of the School of Computer Science and Technology, HUST. Her research interests include computer architecture, massive storage systems, and parallel file systems. She has more than 100 publications in major journals and international conferences, including IEEE-TC, IEEETPDS, ACMTOS, JCST, FAST, USENIX ATC, ICDCS, HPDC, SC, ICS, IPDPS, and ICPP. She serves on the program committees of multiple international conferences, including SC 2011, 2013, and MSST 2012. She is a member of IEEE and a member of ACM.

Yu Hua received the BE and PhD degrees in computer science from Wuhan University, China in 2001 and 2005, respectively. He is an associate professor at the Huazhong University of Science and Technology, China. His research interests include computer architecture, cloud computing, and network storage. He has more than 50 papers to his credit in major journals and international conferences including IEEE Transactions on Computers, IEEE Transactions on Parallel and Distributed Systems, USENIX ATC, INFOCOM, SC, ICDCS, ICPP, and MASCOTS. He has been on the program committees of multiple international conferences, including INFOCOM and ICPP. He is a senior member of the IEEE, and a member of the ACM and USENIX.

Fang Wang received the BE and Master’s degrees in computer science and the PhD degree in computer architecture from the Huazhong University of Science and Technology (HUST), China. She is a professor of computer science and engineering at HUST. Her interests include distribute file systems, parallel I/O storage systems, and graph processing systems.

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Li, C., Feng, D., Hua, Y. et al. A high-performance and endurable SSD cache for parity-based RAID. Front. Comput. Sci. 13, 16–34 (2019). https://doi.org/10.1007/s11704-017-6523-9

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