US 2025/0165397 A1 · GROUPING OF MEMORY CELLS USING A MACHINE LEARNING MODEL RELATED APPLICATION

Abstract

A controller may determine, using a machine learning model, reliability characteristic data associated with memory cells of a non-volatile memory device. The machine learning model may be trained using characterization data that identifies different reliability characteristic of one or more non-volatile memory devices. The controller may group, based on the reliability characteristic data, a first portion of the memory cells of the non-volatile memory device in a first management group, and a second portion of the memory cells of the non-volatile memory device in a second management group. The controller may manage, based on the reliability characteristic data, background scanning and logical to physical mapping of the first management group of memory cells, and the second management group of memory cells.

Claims20

Dependent claims

A method comprising:

determining, using a machine learning model, reliability characteristic data associated with memory cells of a non-volatile memory device;
grouping, based on the reliability characteristic data, a first portion of the memory cells of the non-volatile memory device in a first management group, and a second portion of the memory cells of the non-volatile memory device in a second management group;
and
managing, based on the reliability characteristic data, background scanning or logical to physical mapping of the first management group of memory cells, and the second management group of memory cells.

1 more element

A solid-state drive (SSD), comprising:

a non-volatile memory device;
and
a controller to:
determine, using a machine learning model, reliability characteristic data associated with wordlines of the non-volatile memory device;
determine, based on the reliability characteristic data, a first group of one or more first wordlines of the non-volatile memory device and a second group of one or more second wordlines of the non-volatile memory device;
and
perform at least one of:
first background scanning of the first group of one or more first wordlines at a first frequency that is different than a second frequency of performing second background scanning of the second group of one or more second wordlines, or
logical to physical mapping of data to the first group of one or more first wordlines or to the second group of one or more second wordlines based on the data being a first type of data or a second type of data.

6 more elements

A non-transitory computer-readable medium storing a set of instructions, the set of instructions comprising:

one or more instructions that, when executed by one or more processors of a one or more devices, cause the one or more devices to:
determine, using a machine learning model, reliability characteristic data associated with wordlines of a non-volatile memory device;
determine, based on the reliability characteristic data, a first group of one or more first wordlines of the non-volatile memory device and a second group of one or more second wordlines of the non-volatile memory device;
and
perform, based on the reliability characteristic data, at least one of:
background scanning of the first group of one or more first wordlines and the second group of one or more second wordlines, or
logical to physical mapping of the first group of one or more first wordlines and the second group of one or more second wordlines.

4 more elements

Dependencies are inferred from the claim text.

Grouping of memory cells using a machine learning model related application

Life of this patent

Grouping of memory cells using a machine learning model related application

Life of this patent

Abstract

Claims20