Neural network processing unit and processing system comprising same

A neural network and processing unit technology, applied in the field of deep learning, can solve the problems of high operating power consumption and slow neural network processing speed, and achieve the effects of fast conversion, full utilization, data processing speed and throughput improvement

Active Publication Date: 2018-03-27
INST OF COMPUTING TECH CHINESE ACAD OF SCI
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Problems solved by technology

[0004] However, in the prior art, the neural network has prob

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  • Neural network processing unit and processing system comprising same
  • Neural network processing unit and processing system comprising same
  • Neural network processing unit and processing system comprising same

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Embodiment Construction

[0026] In order to make the purpose, technical solution, design method and advantages of the present invention clearer, the present invention will be further described in detail through specific embodiments in conjunction with the accompanying drawings. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0027] Typically, a deep neural network is a topology with multiple layers of neural networks, and each layer of neural network has multiple feature layers. For example, for a convolutional neural network, its data processing process consists of multi-layer structures such as convolutional layers, pooling layers, normalization layers, nonlinear layers, and fully connected layers. Among them, the operation process of the convolutional layer is: A K*K two-dimensional weight convolution kernel scans the input feature map. During the scanning process, the weight and the correspon...

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Abstract

The invention provides a neural network processing unit and a processing system comprising the same. The processing unit comprises a multiplying unit module which comprises a multilevel structure forming an assembly line, and is used for executing the multiplying operation of to-be-calculated nerve cells and weight values in a neural network, wherein each level of the structure of the multiplyingunit module complete the suboperation of the multiplying operation of to-be-calculated nerve cells and weight values; and a self-accumulator module which carries out the accumulation of the multiplying operation result of the multiplying unit module based on a control signal, or outputs the accumulation result. The processing unit and the processing system can improve the calculation efficiency ofthe neural network and the resource utilization rate.

Description

technical field [0001] The invention relates to the technical field of deep learning, in particular to a neural network processing unit and a processing system including the processing unit. Background technique [0002] In recent years, deep learning technology has developed rapidly and has been widely used in solving high-level abstract cognitive problems, such as image recognition, speech recognition, natural language understanding, weather prediction, gene expression, content recommendation and intelligent robots. Research hotspots in academia and industry. [0003] Deep neural network is one of the perception models with the highest level of development in the field of artificial intelligence. It simulates the neural connection structure of the human brain by establishing a model, and describes the data characteristics hierarchically through multiple transformation stages, providing images, videos, audios, etc. Large-scale data processing tasks bring breakthrough progr...

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Application Information

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IPC IPC(8): G06N3/04
CPCG06N3/045
Inventor 韩银和闵丰许浩博王颖
Owner INST OF COMPUTING TECH CHINESE ACAD OF SCI
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