TY - JOUR
T1 - Coding for Racetrack Memories
AU - Chee, Yeow Meng
AU - Kiah, Han Mao
AU - Vardy, Alexander
AU - Vu, Van Khu
AU - Yaakobi, Eitan
N1 - Funding Information: Manuscript received June 5, 2017; revised December 25, 2017 and January 22, 2018; accepted February 6, 2018. Date of publication February 19, 2018; date of current version October 18, 2018. Y. M. Chee was supported by the Singapore Ministry of Education under Grant MOE2015-T2-2-086. H. M. Kiah was supported in part by the Singapore Ministry of Education under Grant MOE2015-T2-2-086 and in part by the Singapore Ministry of Education under Grant MOE2016-T1-001-156. A. Vardy was supported by the National Science Foundation under Grants CCF–1405119 and CCF–1719139. E. Yaakobi was supported by the Israel Science Foundation under Grant 1624/14. This paper was presented in part at the 2017 IEEE International Symposium on Information Theory [3]. Publisher Copyright: © 2018 IEEE.
PY - 2018/11
Y1 - 2018/11
N2 - 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.
AB - 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.
KW - Racetrack memory
KW - deletions
KW - run-length limited constrained codes
KW - sticky insertions
UR - https://www.scopus.com/pages/publications/85042197432
U2 - 10.1109/TIT.2018.2807480
DO - 10.1109/TIT.2018.2807480
M3 - Article
SN - 0018-9448
VL - 64
SP - 7094
EP - 7112
JO - IEEE Transactions on Information Theory
JF - IEEE Transactions on Information Theory
IS - 11
M1 - 8294216
ER -