Storage medium reliability level judgment method and system, storage medium, and equipment
A storage system and storage medium technology, applied in the field of level judgment, can solve the problems that storage cannot effectively prevent failure, process differences, and spend a lot of time testing and model building
Active Publication Date: 2021-09-07
FUTUREPATH TECH
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Problems solved by technology
This method uses test data to obtain a part of memory reliability decline law, and it takes a lot of time for testing and model building before it has the ability to effectively prevent failures
At the same time, due to the problem of process differences in the manufacturing process, even different memories of the same model have different reliability degradation laws.
The prediction methods currently used can only be applied to the memory types that have been tested and modeled, and cannot effectively prevent failures for memory types that have not been modeled
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[0045] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.
[0046] The embodiment of the present invention provides a method for judging the reliability level of a storage medium. figure 1 It can be known that the method for judging the reliability level of the storage medium provided by the embodiment of the present invention may at least include the following steps S101-S103.
[0047] S101. Obtain the system storage status of at least one storage unit in the storage system, transmit the s...
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The present invention provides a storage medium reliability level judgment method and system based on reinforcement learning, a storage medium, and a computing device. The method includes: acquiring the system storage status of at least one storage unit in the storage system, and transmitting the system storage status to an agent The agent determines the reliability level judgment action corresponding to the storage unit based on the system storage state; the accuracy evaluation of the reliability level judgment action is performed by the storage system to obtain the evaluation result, and the evaluation feedback parameter is generated according to the evaluation result; the evaluation feedback parameter is transmitted To the agent, the agent is optimized and updated based on the evaluation feedback parameters. Based on the solution provided by the present invention, dynamic optimization can be performed according to the actual operating environment, which is applicable to different types of storage media, and the relationship between the reliability of the storage media and the characteristic parameters does not need to be obtained through pre-testing.
Description
technical field [0001] The invention relates to the technical field of flash memory life prediction, in particular to a storage medium reliability level judgment method and system based on reinforcement learning, a storage medium, and a computing device. Background technique [0002] With the development of electronic technology, memory, as the carrier of data stored in electronic equipment, has become more and more important in modern life. Reduced reliability has always been one of the major problems with data storage. During the use of the memory, various errors will occur in the data stored in its unit, which will eventually lead to the failure of the storage unit. If the storage medium generates uncorrectable data errors during operation, it will affect the normal use of the entire storage system, and even lead to loss of important data. . [0003] In order to prevent the failure of the memory, some chips are tested in the field at present, and a prediction model is e...
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IPC IPC(8): G06F3/06
CPCG06F3/0616G06F3/0652G06F3/0653
Inventor 潘玉茜张浩明刘政林
Owner FUTUREPATH TECH