Data processing method, model optimization device and model execution device

A data processing and model technology, applied in the direction of electrical digital data processing, multi-programming devices, biological neural network models, etc., can solve the problems of long model loading time, large pre-computing time, etc., to reduce memory multiplexing calculations , the effect of reducing the load time

Pending Publication Date: 2021-03-19
HUAWEI TECH CO LTD
View PDF2 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] It can be seen that the existing technology pre-calculates the memory required for the operation of the neural network model based on the memory allocation and multiplexing algorithms deployed on the smart device, thereby achieving the purpose of reducing the number of memory allocation and release operations. However, when the resources of the smart device are limited , it takes a lot of precomputation time, causing the model to load too long

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
  • Data processing method, model optimization device and model execution device
  • Data processing method, model optimization device and model execution device
  • Data processing method, model optimization device and model execution device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0053] The embodiment of the present application provides a data processing method, which is used to reduce memory waste when the neural network model is running, reduce the allocation time of memory allocation and release, and can also reduce the loading time of the neural network model.

[0054] A neural network model refers to programs and data that are trained on a large amount of labeled data to perform cognitive computing. The neural network model includes neural network architecture components and neural network parameter components. Wherein, the neural network architecture component refers to the network and its hierarchical structure related to the neural network algorithm in the neural network model, that is, the program used to perform cognitive computing in the above-mentioned neural network model. The neural network model can be used to perform reasoning operations. The process of reasoning operations is to convert input data into outputs through multi-layer opera...

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

The embodiment of the invention discloses a data processing method in the field of artificial intelligence, which is used for reducing the loading duration of a neural network model. The method provided by the embodiment of the invention comprises the steps of obtaining a neural network model; determining a memory size of a memory space required for reasoning operation based on the neural networkmodel; and updating the neural network model to obtain a target neural network model, the target neural network model carrying information indicating the memory size.

Description

technical field [0001] The present application relates to the field of artificial intelligence, in particular to a data processing method, a model optimization device and a model execution device. Background technique [0002] Deep Learning (DL) is an important technology in the field of Artificial Intelligence (AI). DL can usually be divided into two processes: Training and Inference. In the training process, a large amount of sample data is input, and a complex deep neural network model is trained by using unsupervised learning methods such as reinforcement learning. The reasoning process uses the trained model and new data to "reason" various conclusions. For example, the video surveillance equipment judges whether a captured face belongs to the blacklist through the trained deep neural network model. Due to the huge amount of training data and complex deep neural network structure involved in the training process, the calculation is huge, and it is usually completed by...

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 Applications(China)
IPC IPC(8): G06N3/063G06N3/04G06F9/50
CPCG06N3/063G06F9/5016G06N3/045G06N3/04G06F9/50
Inventor 张臻鲍翀袁鹏
Owner HUAWEI 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