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RFTL: improving performance of selective caching-based page-level FTL through replication
  • Mativenga, Ronnie ;
  • Paik, Joon Young ;
  • Kim, Youngjae ;
  • Lee, Junghee ;
  • Chung, Tae Sun
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Publication Year
2019-03-15
Publisher
Springer New York LLC
Citation
Cluster Computing, Vol.22, pp.25-41
Keyword
Cached mapping tableFlash memoryFlash translation layerSolid-state drive
Mesh Keyword
Cached mapping tableCumulative distribution functionExperimental evaluationFlash translation layerImproving performanceSolid state drivesSynthetic workloadsWorkload characteristics
All Science Classification Codes (ASJC)
SoftwareComputer Networks and Communications
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.
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/30306
DOI
https://doi.org/10.1007/s10586-018-2824-5
Fulltext

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