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

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

Research output: Contribution to journalArticle

5 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)25-41
Number of pages17
JournalCluster Computing
Volume22
Issue number1
DOIs
Publication statusPublished - 2019 Mar 15
Externally publishedYes

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Keywords

  • Cached mapping table
  • Flash memory
  • Flash translation layer
  • Solid-state drive

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications

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