Identifying memory block write endurance using machine learning
US11049009B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 30, 2017 |
| Grant date | Jun 29, 2021 |
| Priority date | — |
| Expiry date | Apr 12, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG11C16/0483
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods are described for predicting an endurance of groups of memory cells within a memory device, based on current characteristics of the cells. The endurance may be predicted by processing historical information regarding operation of memory devices according to a machine learning algorithm, such as a neural network algorithm, to generate correlation information between characteristics of groups of memory calls at a first time and an endurance metric at a second time. The correlation information can be applied to current characteristics of a group of memory cells to predict a future endurance of that group. Operating parameters of a memory device may be modified at a per-block level based on predicted block endurances to increase the speed of a device, the longevity of a device, or both.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.