Endurance-Limited Memories: Capacity and Codes
Yeow Meng Chee, Michal Horovitz, Alexander Vardy, Van Khu Vu, and, Eitan Yaakobi

TL;DR
This paper introduces endurance-limited memory (ELM) codes to extend the lifespan of resistive memories by limiting cell programming, providing capacity characterizations for various knowledge scenarios of encoder and decoder.
Contribution
The paper proposes a new coding scheme called ELM codes that limit cell programming to enhance memory endurance and fully characterizes their capacity regions under different knowledge models.
Findings
Maximum sum-rate is log sum_{i=0}^{\u007f} {t i}
Capacity regions are fully characterized when encoder knows programming counts
Practical model with encoder reading memory before encoding is analyzed
Abstract
\emph{Resistive memories}, such as \emph{phase change memories} and \emph{resistive random access memories} have attracted significant attention in recent years due to their better scalability, speed, rewritability, and yet non-volatility. However, their \emph{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 \emph{endurance-limited memories} (\emph{ELM}) codes, that increases the endurance of these memories by limiting the number of cell programming operations. Namely, an \emph{-change -write ELM code} is a coding scheme that allows to write messages into some binary cells while guaranteeing that each cell is programmed at most times. In case , these codes coincide with the…
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