Encoding type flash memory device and encoding method

Abstract

The invention discloses a coding type flash memory device and a coding method, wherein the coding type flash memory device comprises: at least one flash memory array structural unit, multiple comparators and multiple adders, each flash memory array in the at least one flash memory array structural unit The structural unit is a 3D NAND FLASH array structural unit, which is used to implement an encoding operation to generate a source line voltage on each of the multiple source lines of the flash memory array structural unit; each of the multiple comparators is related to each source. The lines are correspondingly connected, and are used to convert the source line voltage of each source line correspondingly connected to an output result in a binary form; and each adder in the plurality of adders corresponds to at least 2 of the plurality of comparators Each of the source lines of , is connected to each other, and is used to perform sum operation on at least two output results corresponding to at least two comparators. The coded flash memory device and the coding method of the present invention can realize efficient and accurate full-connection layer or convolutional layer operations, thereby realizing a deep neural network.

Description

technical field [0001] The present invention relates to the technical field of semiconductor devices and integrated circuits, in particular to a coding flash memory device and coding method for realizing a deep neural network. Background technique [0002] Deep neural networks are currently widely used in image processing and speech recognition and have shown excellent performance. Most of the deep neural networks in the prior art rely on the traditional von Neumann architecture to perform operations, but due to the separation of storage units and computing units in the von Neumann computing architecture, data transmission through the bus will cause delays. The increase of energy consumption and the increase of energy consumption make the data processing capacity and energy efficiency ratio improvement of deep neural network bottlenecks. To this end, the prior art further proposes an encoded flash memory device that performs analog operations based on a 3D NAND FLASH struct...

AI Technical Summary

Problems solved by technology

[0007] In order to solve the technical problems of low calculation accuracy, low energy efficiency ratio, non-maximized computing architecture efficiency, and unsaturated parallelism in the encoded flash memory device that performs analog operations based on the 3D NAND FLASH structure in the prior art, the present invention provides An encoded flash memory device and encoding method

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