Machine-learning-based system health monitoring of a memory device

Abstract

A system includes a memory device comprising multiple dies and a processing device coupled to the memory device. The processing device causes a health scan to be performed on a block family of the multiple dies. The processing device updates, for each read sample taken during the health scan, an assignment to a voltage offset bin of a plurality of voltage offset bins. The processing device provides the updated assignments to the plurality of voltage offset bins to a machine learning trigger rate (TR) model. The processing device receives, from the machine learning TR model, a code word error rate (CWER) distribution of the memory device. In response to determining that a TR margin value associated with the CWER distribution does not satisfy a threshold value, the processing device causes a data associated with the block family to be refreshed.