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

Authors
이중희
Issue Date
Mar-2019
Publisher
SPRINGER
Citation
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, v.22, no.1, pp.25 - 41
Indexed
SCIE
SCOPUS
Journal Title
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
Volume
22
Number
1
Start Page
25
End Page
41
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/139691
ISSN
1386-7857
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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