Algorithms and data structures for flash memories

By E. Gal, Sivan Toledo. CSUR, 2005

657 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Hardware and Architecture

View Paper: https://www.semanticscholar.org/paper/94aaabc634c42bbcccaee9314218e710cfb01fe4

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Citations in the corpus

SCORE (2018, background): “The key functions of the FTL include address mapping, garbage collection, and wear leveling [20].”
Error Characterization, Mitigation, and Recovery in Flash-Memory-Based Solid-State Drives (2017, methodology): “One simple approach is to select the block in the free list with the lowest number of P/E cycles to minimize the variance of the wearout amount across blocks, though many algorithms have been developed for wear leveling [34, 54].”
Performance impact and interplay of SSD parallelism through advanced commands, allocation strategy and data granularity (2011, background): “The top module is responsible for buffer organization and scheduling requests; In the middle module, the FTL sub-module simulates many state-of-the-art FTL schemes including pure page-FTL [43][44], pure block-FTL [43][44], DFTL [12] and FAST [15], and the allocation sub-module provides the choice of”
Consistent and Durable Data Structures for Non-Volatile Byte-Addressable Memory (2011, background): “Recently there have been many efforts [21] to optimize data structures for flash memory based systems.”
Understanding intrinsic characteristics and system implications of flash memory based solid state drives (2009, background): “Our study reveals several unanticipated aspects in the performance dynamics of SSD technology that must be addressed by system designers and data-intensive application users in order to e.ectively place it in the storage hierarchy.”
Enhancing lifetime and security of PCM-based Main Memory with Start-Gap Wear Leveling (2009, background): “1 Related Work in Wear Leveling Wear leveling has been studied extensively for Flash based storage structures [7][12][2][3][6].”
Design of flash-based DBMS: an in-page logging approach (2007, background): “Due to no mechanical latency of flash memory, however, small random writes can be processed efficiently as long as costly erase operations are not involved [8].”
Error patterns in MLC NAND flash memory: Measurement, characterization, and analysis (2012, background): “Assuming typical write amplification of 2 times (due to additional writes caused by garbage collection and wear leveling [4]) and ideal wear-leveling, current MLC flash based storage will use up all its reliable P/E cycles (e.”
ChunkStash: Speeding Up Inline Storage Deduplication Using Flash Memory (2010, methodology): “FTL uses various wear leveling techniques to even out the erase counts of different blocks in the flash memory to increase its overall longevity [20].”
CAFTL: A Content-Aware Flash Translation Layer Enhancing the Lifespan of Flash Memory based Solid State Drives (2011, background): “Most previous research work [21] focuses on the third factor, garbage collection and wear-leveling policies.”