Feature extraction method, device and equipment and storage medium

Abstract

The invention discloses a feature extraction method, device and equipment and a storage medium. The method comprises the steps: receiving a read-write instruction sent by a user, and extracting an LBAaddress contained in the read-write instruction as a target address; determining an address range to which the destination address belongs as a destination range; wherein the address range is obtained by dividing all LBA addresses contained in the storage device in advance; judging the access frequency corresponding to the target range updated last time to the current moment; whether the frequency of extracting the LBA address belonging to the target range from the received read-write instruction reaches a frequency threshold value or not is judged, if yes, the access frequency correspondingto the target range is updated to be the value obtained by adding a preset value to the current value, and if not, it is determined that the access frequency corresponding to the target range does notneed to be updated. According to the method, the data volume corresponding to the features can be greatly reduced, so that the calculation amount can be reduced while the corresponding storage spaceis reduced.

Description

technical field [0001] The present invention relates to the technical field of solid-state hard drives, and more specifically, to a feature extraction method, device, equipment and storage medium. Background technique [0002] Solid state disk SSD has the advantages of high performance and low power consumption, and is a device used to store user data. The solid-state hard disk is composed of modules such as a controller and a storage medium NAND. The controller runs related software to control resources in the storage medium, schedule user data storage, and maintain the storage medium. [0003] The reading and writing behaviors of different users are different, the reading and writing behaviors of different application software run by the same user are different, and the reading and writing behaviors of running the same application software at different times are also different. Solid-state drives generally have no way to perform special optimization for different read and...

AI Technical Summary

Problems solved by technology

[0004] Artificial intelligence is generally divided into feature extraction, classifier modeling, training, decision-making and other processes. Feature data is important information in this process, but due to the large amount of data and the consumption of computing power, it has a negative impact on the application of artificial intelligence algorithms.

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