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RFTL: improving performance of selective caching-based page-level FTL through replication

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Abstract

The internal nature of flash memory technology, makes its performance highly dependent on workload characteristics causing poor performance on random writes. To solve this, Demand-based Flash Translation Layer (DFTL) which selectively caches page-level address mappings, was proposed. DFTL exploits temporal locality in workloads and when low, high cache miss rates are experienced. In this paper, we propose a replication based DFTL, called RFTL, which aims at minimizing the overhead caused by miss penalty from the cached mapping table in SRAM. We developed an analytical model for studying the range of performance for RFTL. We extended EagleTree simulator to implement RFTL. Our experimental evaluation with synthetic workloads endorses the utility of RFTL showing improved performance over DFTL especially for read-dominant workloads. With 80% read dominant workload, RFTL’s cumulative distribution function shows a 20% improvement and under 80% write dominant workload, it outperforms DFTL by 10% on I/O throughput.

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Acknowledgements

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2015R1C1A1A01052105).

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Authors and Affiliations

  1. Ajou University, Suwon, 443-749, South Korea

    Ronnie Mativenga, Joon-Young Paik & Tae-Sun Chung

  2. Sogang University, Seoul, 13557, South Korea

    Youngjae Kim

  3. University of Texas at San Antonio, San Antonio, TX, 78249, USA

    Junghee Lee

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  1. Ronnie Mativenga
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  2. Joon-Young Paik
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  3. Youngjae Kim
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  4. Junghee Lee
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  5. Tae-Sun Chung
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Correspondence to Youngjae Kim.

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Mativenga, R., Paik, JY., Kim, Y. et al. RFTL: improving performance of selective caching-based page-level FTL through replication. Cluster Comput 22, 25–41 (2019). https://doi.org/10.1007/s10586-018-2824-5

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