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HybridPlan: a capacity planning technique for projecting storage requirements in hybrid storage systems

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Abstract

Economic forces, driven by the desire to introduce flash into the high-end storage market without changing existing software-base, have resulted in the emergence of solid-state drives (SSDs), flash packaged in HDD form factors and capable of working with device drivers and I/O buses designed for HDDs. Unlike the use of DRAM for caching or buffering, however, certain idiosyncrasies of NAND Flash-based solid-state drives (SSDs) make their integration into hard disk drive (HDD)-based storage systems nontrivial. Flash memory suffers from limits on its reliability, is an order of magnitude more expensive than the magnetic hard disk drives (HDDs), and can sometimes be as slow as the HDD (due to excessive garbage collection (GC) induced by high intensity of random writes). Given the complementary properties of HDDs and SSDs in terms of cost, performance, and lifetime, the current consensus among several storage experts is to view SSDs not as a replacement for HDD, but rather as a complementary device within the high-performance storage hierarchy. Thus, we design and evaluate such a hybrid storage system with HybridPlan that is an improved capacity planning technique to administrators with the overall goal of operating within cost-budgets. HybridPlan is able to find the most cost-effective hybrid storage configuration with different types of SSDs and HDDs

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Notes

  1. A similar gap exists between SSD and DRAM. Furthermore, this rules out major changes in the role played by DRAM in future systems that employ SSDs. DRAM will continue to retain both of its important roles related to caching and buffering. Therefore, we will not compare these two devices in the rest of this paper.

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Acknowledgements

We would like to thank the anonymous reviewers for their detailed comments, which helped us improve the quality of this paper. This research was funded in part by NSF grant CCF-0811670. It was also supported in part by, and used the resources of, the Oak Ridge Leadership Computing Facility, located in the National Center for Computational Sciences at ORNL, which is managed by UT Battelle, LLC for the U.S. DOE (under the contract No. DE-AC05-00OR22725).

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Authors and Affiliations

  1. National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA

    Youngjae Kim

  2. IBM Almaden Research, San Jose, CA, USA

    Aayush Gupta

  3. Department of Computer Science and Engineering, Pennsylvania State University, University Park, PA, USA

    Bhuvan Urgaonkar, Piotr Berman & Anand Sivasubramaniam

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  1. Youngjae Kim
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  2. Aayush Gupta
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  3. Bhuvan Urgaonkar
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  4. Piotr Berman
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  5. Anand Sivasubramaniam
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Correspondence to Youngjae Kim.

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Kim, Y., Gupta, A., Urgaonkar, B. et al. HybridPlan: a capacity planning technique for projecting storage requirements in hybrid storage systems. J Supercomput 67, 277–303 (2014). https://doi.org/10.1007/s11227-013-0999-3

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