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Coding for Racetrack Memories.

Authors :
Chee, Yeow Meng
Kiah, Han Mao
Vardy, Alexander
Vu, Van Khu
Yaakobi, Eitan
Source :
IEEE Transactions on Information Theory. Nov2018, Vol. 64 Issue 11, p7094-7112. 19p.
Publication Year :
2018

Abstract

Racetrack memory is a new technology, which utilizes magnetic domains along a nanoscopic wire in order to obtain extremely high storage density. In racetrack memory, each magnetic domain can store a single bit of information, which can be sensed by a reading port (head). The memory is structured like a tape, which supports a shift operation that moves the domains to be read sequentially by the head. In order to increase the memory’s speed, prior work studied how to minimize the latency of the shift operation, while the no less important reliability of this operation has received only a little attention. In this paper, we design codes, which combat shift errors in racetrack memory, called position errors, namely, shifting the domains is not an error-free operation and the domains may be over shifted or are not shifted, which can be modeled as deletions and sticky insertions. While it is possible to use conventional deletion and insertion-correcting codes, we tackle this problem with the special structure of racetrack memory, where the domains can be read by multiple heads. Each head outputs a noisy version of the stored data and the multiple outputs are combined in order to reconstruct the data. This setup is a special case of the reconstruction problem studied by Levenshtein, however, in our case, the position errors from different heads are correlated. We will show how to take advantage of this special feature of racetrack memories in order to construct codes correcting deletions and sticky insertions. In particular, under this paradigm, we will show that it is possible to correct, with at most a single bit of redundancy, $d$ deletions with $d+1$ heads if the heads are well separated. Similar results are provided for burst of deletions, sticky insertions, and combinations of both deletions and sticky insertions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00189448
Volume :
64
Issue :
11
Database :
Academic Search Index
Journal :
IEEE Transactions on Information Theory
Publication Type :
Academic Journal
Accession number :
132546129
Full Text :
https://doi.org/10.1109/TIT.2018.2807480