A Constraint Scheme for Correcting Massive Asymmetric Magnitude-1 Errors in Multi-Level NVMs




Abstract: We present a constraint-coding scheme to correct large numbers of asymmetric magnitude-1 errors in multi-level non-volatile memories. The scheme is shown to deliver better correction capability compared to known alternatives, while admitting low-complexity of decoding. Another advantage of this scheme is the flexibility to vary the code parameters without significant modifications. This is especially attractive for dealing with manufacturing variability and wear-induced device degradation.

Bio: Yuval Cassuto is a faculty member and a Viterbi computer-engineering fellow at the Department of Electrical Engineering of the Technion - Israel Institute of Technology. His research interests include coding theory, coding techniques for data storage, memory and storage architectures+algorithms, and data distribution in networks. His work on coding for flash memories has won the IEEE Communications Society's 2010 best student paper award in data storage.