Reverse operation sparse method of neural network and related product

Abstract

The invention provides a reverse operation sparse method of a neural network and a computing chip. The method is used for executing sparse processing in neural network operation and then performing reverse operation. The technical scheme provided by the invention has the advantages of small calculation amount and low power consumption.

Description

technical field [0001] The present disclosure relates to the field of neural networks, in particular to a neural network reverse operation sparse method and related products. Background technique [0002] Artificial Neural Network (ANN) is a research hotspot in the field of artificial intelligence since the 1980s. It abstracts the human brain neuron network from the perspective of information processing, establishes a simple model, and forms different networks according to different connection methods. In engineering and academia, it is often referred to directly as a neural network or a neural network. A neural network is an operational model consisting of a large number of nodes (or neurons) connected to each other. The reverse operation of the existing neural network is based on the calculation of the original data such as the reverse input data and weights to obtain the corresponding results. The calculation of such original data requires a large amount of calculation ...

AI Technical Summary

Problems solved by technology

The reverse operation of the existing neural network is based on the calculation of the original data such as the reverse input data and weights to obtain the corresponding results. The calculation of such original data requires a large amount of calculation and high power consumption.

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