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Published in: Cluster Computing 1/2019

25-07-2018

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

Authors: Ronnie Mativenga, Joon-Young Paik, Youngjae Kim, Junghee Lee, Tae-Sun Chung

Published in: Cluster Computing | Issue 1/2019

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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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Metadata
Title
RFTL: improving performance of selective caching-based page-level FTL through replication
Authors
Ronnie Mativenga
Joon-Young Paik
Youngjae Kim
Junghee Lee
Tae-Sun Chung
Publication date
25-07-2018
Publisher
Springer US
Published in
Cluster Computing / Issue 1/2019
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-018-2824-5

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