Memory device based on phase change memory for deep neural network and method for storing weight thereof

Abstract

The present disclosure provides a PCM-based memory device for DNN and a method for storing weights thereof, the device comprising: a cell array having a plurality of memory cells implemented with phase change memories (Multi-Level Cell-Phase Change Memory, hereinafter PCM) that each store multi-bit data according to a resistance state level including a resistance value among a plurality of resistance state levels; and a memory controller that stores multi-bit data in the memory cells by mapping each bit pattern and the resistance state level, according to an appearance rate for bit patterns of a plurality of weights included in a plurality of layers constituting a DNN (Deep Neural Network). According to the present disclosure, fault tolerance can be improved by reducing the frequency of data errors due to resistance drift phenomenon.