Flash memory reliability level online prediction method and device based on dynamic neural network

Abstract

The invention discloses a flash memory reliability level online prediction method and device based on a dynamic neural network, a storage medium and computer equipment. The method comprises the following steps: performing flash memory operation on a to-be-predicted flash memory chip, and collecting at least one characteristic quantity of the to-be-predicted flash memory chip in the flash memory operation process; computing at least one characteristic quantity of the to-be-predicted flash memory chip to obtain a characteristic operation value of the to-be-predicted flash memory chip, and constructing a data set of the to-be-predicted flash memory chip according to the characteristic quantity of the to-be-predicted flash memory chip and the characteristic operation value of the to-be-predicted flash memory chip; taking a first subset in the data set of the to-be-predicted flash memory chip as input of a dynamic neural network, running the dynamic neural network to obtain a first flash memory reliability level prediction model, and obtaining an initial reliability level prediction result through the first flash memory reliability level prediction model; according to the initial reliability grade prediction result and an actual reliability grade test result of the to-be-predicted flash memory chip, optimizing model parameters of the first flash memory reliability grade prediction model to obtain a second flash memory reliability grade prediction model; and inputting a second subset in the to-be-predicted flash memory chip data set into the second flash memory reliability level prediction model to obtain a prediction result of the reliability level of the to-be-predicted flash memory chip. According to the method, the prediction accuracy and flexibility of the reliability level of the flash memory chip can be improved.

Description

technical field [0001] The present invention relates to the technical field of memory, in particular to an online prediction method, device, storage medium and computer equipment of flash memory reliability level based on a dynamic neural network. Background technique [0002] With the rapid development of science and technology, the demand for data storage is also growing explosively. After decades of technological updates, flash memory has continuously expanded its storage capacity and greatly reduced the price per bit. At the same time, it has gradually replaced magnetic media with its large storage capacity, faster read and write performance, and better antimagnetic and shockproof capabilities. The mainstream non-volatile memory is playing an increasingly important role in civil, industrial, military and other fields. [0003] On the other hand, while the capacity and integration of flash memory continue to increase, the reliability of flash memory is also becoming incr...

AI Technical Summary

Problems solved by technology

[0004] In view of this, the present application provides an online prediction method, device, storage medium and computer equipment for flash memory reliability level based on dynamic neural network. Technical Issues of Flexible Application of Flash Memory Chip Reliability Prediction Method

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