Data processing method and device, AI chip, electronic equipment and storage medium

Abstract

The invention relates to a data processing method and device, an AI chip, electronic equipment and a storage medium, and belongs to the technical field of neural networks. The data processing method comprises the following steps: acquiring basic information of a neural network deployed in an AI chip and basic information of the AI chip; selecting an optimal compression algorithm from a plurality of preset compression algorithms according to the basic information of the neural network and the basic information of the AI chip; the related data of the neural network are compressed through an optimal compression algorithm, compressed data and corresponding data indexes are obtained, and the data indexes are used for reducing the compressed data into original data before compression or used for determining the positions of non-zero elements in the compressed data in the original data before compression. By combining the specific conditions of the neural network and the AI chip, the compression scheme suitable for the current scene is flexibly selected, acceleration of the sparse neural network is completed in a relatively optimal mode, and the energy consumption ratio and the performance are improved.

Description

technical field [0001] The present application belongs to the technical field of neural networks, and specifically relates to a data processing method, an apparatus, an AI chip, an electronic device and a storage medium. Background technique [0002] With the advent of the era of artificial intelligence (AI), intelligent tasks such as image recognition, speech recognition, and natural language processing are ubiquitous in life. Neural network, as one of the most effective algorithms to achieve this kind of intelligent task, has received extensive attention and application. However, a large neural network has a large number of layers and nodes, resulting in a large number of weight parameters, time-consuming network training process, and a large storage space for the trained model. Therefore, in the field of artificial intelligence, more and more attention has been paid to sparse neural networks, and many optimization methods have been proposed to obtain greater benefits com...

AI Technical Summary

Problems solved by technology

However, the problem that this method may face is that the dedicated chip may not support the compression and decompression operations of the sparse network; even if the chip supports the sparse network, the compression and decompression scheme used may not be suitable for the current network scenario. make the gains not obvious

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