Back to Search Start Over

Endurance-Limited Memories: Capacity and Codes.

Authors :
Chee, Yeow Meng
Horovitz, Michal
Vardy, Alexander
Vu, Van Khu
Yaakobi, Eitan
Source :
IEEE Transactions on Information Theory; Mar2022, Vol. 68 Issue 3, p1599-1613, 15p
Publication Year :
2022

Abstract

Resistive memories, such as phase change memories and resistive random access memories have attracted significant attention in recent years due to their better scalability, speed, rewritability, and yet non-volatility. However, their limited endurance is still a major drawback that has to be improved before they can be widely adapted in large-scale systems. In this work, in order to reduce the wear out of the cells, we propose a new coding scheme, called endurance-limited memories (ELM) codes, that increases the endurance of these memories by limiting the number of cell programming operations. Namely, an $\ell $ -change $t$ -write ELM code is a coding scheme that allows to write $t$ messages into some $n$ binary cells while guaranteeing that each cell is programmed at most $\ell $ times. In case $\ell =1$ , these codes coincide with the well-studied write-once memory (WOM) codes. We study some models of these codes which depend upon whether the encoder knows on each write the number of times each cell was programmed, knows only the memory state, or even does not know anything. For the decoder, we consider these similar three cases. We fully characterize the capacity regions and the maximum sum-rates of three models where the encoder knows on each write the number of times each cell was programmed. In particular, it is shown that in these models the maximum sum-rate is $\log \sum _{i=0}^{\ell } {\binom{t }{ i}}$. We also study and expose the capacity regions of the models where the decoder is informed with the number of times each cell was programmed. Finally we present the most practical model where the encoder read the memory before encoding new data and the decoder has no information about the previous states of the memory. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00189448
Volume :
68
Issue :
3
Database :
Complementary Index
Journal :
IEEE Transactions on Information Theory
Publication Type :
Academic Journal
Accession number :
155458623
Full Text :
https://doi.org/10.1109/TIT.2021.3132995