Adaptive Threshold Read Algorithms in Multi-Level Non-Volatile Memories

Abstract

For an array of memory cells that are read by threshold measurements, we ask the question of how to choose the measurements in the read sequence to minimize the number of measurements before the array is fully read. We propose and study analytically and experimentally various adaptive read algorithms, and provide corresponding lower bounds on the average number of measurements. We show that new two-dimensional read algorithms improve over the best one-dimensional ones. We further adapt the read algorithms to the case where the cell levels are not uniformly distributed, as motivated by partially-erased memory arrays.