DocumentCode :
3541528
Title :
Probabilistic graphical model for flash memory programming
Author :
Peleato, Borja ; Agarwal, Rajiv ; Cioffi, John
Author_Institution :
Electr. Eng. Dept., Stanford Univ., Stanford, CA, USA
fYear :
2012
fDate :
5-8 Aug. 2012
Firstpage :
788
Lastpage :
791
Abstract :
Flash memory presents significant advantages over hard drives in terms of read speed and power efficiency; however its lifetime can be several orders of magnitude smaller. Thus increasing lifetime of flash memory via signal processing techniques is an important research area. The first half of the paper presents a statistical method for estimating the health of the cells in a Flash memory, based on which a variable error correction coding scheme can be used to increase lifetime. The second half of the paper proposes a statistical approach to increase lifetime when the flash controller can dynamically vary the program and erase operation strategy. This approach uses Markov Decision Processes (MDP) to choose the optimal program or erase strategy at any given point in the life of a Flash memory based on its current state or health. From a bigger picture stand-point, the paper presents a novel way of flash management using a Markov model for health of the memory at any given point in its lifetime.
Keywords :
Markov processes; error correction codes; flash memories; signal processing; statistical analysis; MDP; Markov decision processes; erase strategy; flash controller; flash management; flash memory programming; optimal program; power efficiency; probabilistic graphical model; read speed; signal processing techniques; statistical approach; variable error correction coding scheme; Ash; Dielectrics; Flash memory; Graphical models; Hidden Markov models; Markov processes; Probabilistic logic; Flash memories; Markov decision process; hidden Markov model; probabilistic graphical model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Statistical Signal Processing Workshop (SSP), 2012 IEEE
Conference_Location :
Ann Arbor, MI
ISSN :
pending
Print_ISBN :
978-1-4673-0182-4
Electronic_ISBN :
pending
Type :
conf
DOI :
10.1109/SSP.2012.6319823
Filename :
6319823
Link To Document :
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