Storage System and Method for Implementation of Symmetric Tree Models for Read Threshold Calibration

Abstract

A storage system has an inference engine that can infer a read threshold based on a plurality of parameters of the memory. The read threshold can be used in reading a wordline in the memory during a regular read operation or as part of an error handling process. Using this machine-learning-based approach to infer a read threshold can provide significant improvement in read threshold accuracy, which can reduce bit error rate and improve latency, throughput, power consumption, and quality of service. In another embodiment, a storage system is configured to use a binary full-depth symmetrically-sorted tree to infer a read threshold based on a plurality of parameters of the memory.

Dependencies are inferred from the claim text.