RFTL: improving performance of selective caching-based page-level FTL through replication
- Authors
- 이중희
- Issue Date
- 3월-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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Collections - School of Cyber Security > Department of Information Security > 1. Journal Articles
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