Computing device and related products, computing method for executing artificial neural network model

A computing device and neuron technology, applied in the field of artificial neural network, can solve the problems of high power consumption, large power consumption, and no multi-layer artificial neural network operation.

Active Publication Date: 2020-12-11
ANHUI CAMBRICON INFORMATION TECH CO LTD
View PDF7 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Since the GPU is a device specially used to perform graphics and image calculations and scientific calculations, without special support for multi-layer artificial neural network operations, it still requires a lot of front-end decoding work to perform multi-layer artificial neural network operations, which brings a lot of problems. additional cost
In addition, the GPU only has a small on-chip cache, and the model data (weights) of the multi-layer artificial neural network need to be repeatedly moved from off-chip, and the off-chip bandwidth has become the main performance bottleneck.
In addition, the GPU has only a small on-chip cache, and the model data (weights) of the multi-layer artificial neural network need to be repeatedly moved from off-chip. The off-chip bandwidth has become the main performance bottleneck, and it has brought huge power consumption overhead.
[0013] Therefore, using the above-mentioned traditional technology to perform self-learning operations on multi-layer artificial neural networks, the power consumption overhead is relatively high

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Computing device and related products, computing method for executing artificial neural network model
  • Computing device and related products, computing method for executing artificial neural network model
  • Computing device and related products, computing method for executing artificial neural network model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0073] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

[0074] In one example, please also refer to figure 1 and Figure 4 , this embodiment provides a computing device, and the computing device is used for performing artificial neural network operations. The computing device includes: a controller unit 11 and a computing unit 12 , wherein the controller unit 11 is connected to the computing unit 12 . The arithmetic unit 12 includes: a main processing circuit 101 and a plurality of slave processing circuits 102; the main processing circuit 101 includes: an addition processing circuit 101a, an activation processing circuit 101...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

This application relates to a computing device and related products, and a computing method for executing an artificial neural network model. Compared with general processors and image processors, the computing device can improve the computing speed of self-learning computing, save computing time, and further reduce power consumption.

Description

technical field [0001] The present application relates to the technical field of artificial neural network, in particular to a computing device and related products, and a computing method for executing an artificial neural network model. Background technique [0002] Multi-layer artificial neural networks are widely used in the fields of pattern recognition, image processing, function approximation, and optimization calculations. In recent years, multi-layer artificial networks have been favored by academic circles and researchers due to their high recognition accuracy and good parallelism. industry is getting more and more attention. [0003] The self-learning operation of multi-layer artificial neural network is a very important link in the operation process of multi-layer artificial neural network. At present, the self-learning pre-training of multi-layer artificial neural networks adopts a layer-by-layer training method. For each layer, the pre-training is divided into...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/04G06N3/08G06F9/30G06F9/38
CPCG06N3/084G06F9/30007G06F9/3885G06N3/044G06N3/045
Inventor 不公告发明人
Owner ANHUI CAMBRICON INFORMATION TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap