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An efficient page-level FTL to optimize address translation in flash memory

Published: 17 April 2015 Publication History
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  • Abstract

    Flash-based solid state disks (SSDs) have been very popular in consumer and enterprise storage markets due to their high performance, low energy, shock resistance, and compact sizes. However, the increasing SSD capacity imposes great pressure on performing efficient logical to physical address translation in a page-level flash translation layer (FTL). Existing schemes usually employ a built-in RAM cache for storing mapping information, called the mapping cache, to speed up the address translation. Since only a fraction of the mapping table can be cached due to limited cache space, a large number of extra operations to flash memory are required for cache management and garbage collection, degrading the performance and lifetime of an SSD. In this paper, we first apply analytical models to investigate the key factors that incur extra operations. Then, we propose an efficient page-level FTL, named TPFTL, which employs two-level LRU lists to organize cached mapping entries to minimize the extra operations. Inspired by the models, we further design a workload-adaptive loading policy combined with an efficient replacement policy to increase the cache hit ratio and reduce the writebacks of replaced dirty entries. Finally, we evaluate TPFTL using extensive trace-driven simulations. Our evaluation results show that compared to the state-of-the-art FTLs, TPFTL reduces random writes caused by address translation by an average of 62% and improves the response time by up to 24%.

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    cover image ACM Conferences
    EuroSys '15: Proceedings of the Tenth European Conference on Computer Systems
    April 2015
    503 pages
    ISBN:9781450332385
    DOI:10.1145/2741948
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 17 April 2015

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    • (2023)Optimizing the Cost of Garbage Collection in F2FS Using Working Set StrategyHighlights in Science, Engineering and Technology10.54097/hset.v39i.667339(896-901)Online publication date: 1-Apr-2023
    • (2022)ICE: An Intelligent Cognition Engine with 3D NAND-based In-Memory Computing for Vector Similarity Search Acceleration2022 55th IEEE/ACM International Symposium on Microarchitecture (MICRO)10.1109/MICRO56248.2022.00058(763-783)Online publication date: Oct-2022
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