Deep learning based program-verify modeling and voltage estimation for memory devices

A system for improving performance of a memory device, comprising:

• a processor and a memory including instructions stored thereupon, wherein the instructions upon execution by the processor cause the processor to:
• obtain a plurality of cell counts for each of a plurality of read voltages applied to the memory device, wherein each of the plurality of read voltages corresponds to a program verify (PV) state, and wherein each of the plurality of cell counts represents a number of cells having a cell voltage value that is within a voltage band corresponding to the read voltage applied thereto;
• generate, based on the plurality of cell counts and the plurality of read voltages, at least one ones count, at least one checksum, and a plurality of samples corresponding to a distribution function of at least one read voltage of the plurality of read voltages;
• determine an updated value for the at least one read voltage based on an output of a deep neural network (DNN), wherein an input to the DNN comprises the at least one ones count, the at least one checksum, and the plurality of samples;
• and
• apply the updated value of the at least one read voltage to the memory device to retrieve information from the memory device.

A non-transitory computer-readable storage medium having instructions stored thereupon for improving performance of a memory device, comprising:

• instructions for obtaining a plurality of cell counts for each of a plurality of read voltages applied to the memory device, wherein each of the plurality of read voltages corresponds to a program verify (PV) state, and wherein each of the plurality of cell counts represents a number of cells having a cell voltage value that is within a voltage band corresponding to the read voltage applied thereto;
• instructions for generating, based on the plurality of cell counts and the plurality of read voltages, at least one ones count, at least one checksum, and a plurality of samples corresponding to a distribution function of at least one read voltage of the plurality of read voltages;
• instructions for determining an updated value for the at least one read voltage based on an output of a deep neural network (DNN), wherein an input to the DNN comprises the at least one ones count, the at least one checksum, and the plurality of samples;
• and
• instructions for applying the updated value of the at least one read voltage to the memory device to retrieve information from the memory device.