A neural network simulation method and device

A technology of neural network and simulation method, which is applied in the direction of neural learning method, biological neural network model, special data processing application, etc., and can solve problems such as inability to complete multi-layer continuous simulation verification, low efficiency, and inability to automatically obtain data source storage paths , to achieve the effects of saving simulation time, improving simulation efficiency, and simplifying the simulation operation process

Active Publication Date: 2019-05-10
深兰人工智能芯片研究院(江苏)有限公司
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Problems solved by technology

[0007] The present invention provides a simulation method and device of a neural network, which is used to solve the existing simulation verification system for a neural network model of FPGA. When performing simulation, the data source storage path cannot be automatically obtained, so multi-layer continuous simulation verification cannot be completed. inefficiency

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  • A neural network simulation method and device
  • A neural network simulation method and device
  • A neural network simulation method and device

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[0055] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. . Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0056] The following explains some words that appear in the text:

[0057] 1. In the embodiment of the present invention, the term "and / or" describes the association relationship of the associated objects, indicating that there can be three types of relationships, for example, A and / or B, which can mean that there is A alone, and both A and B exist. There are three cases of B. The character " / " generally indicates that the asso...

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Abstract

The invention discloses a neural network simulation method and device, and aims to solve the problems that multi-layer continuous simulation verification cannot be completed and the efficiency is lowdue to the fact that a storage path of to-be-simulated layer data cannot be automatically acquired during simulation in an existing simulation verification system for a neural network model of an FPGA. According to the embodiment of the invention, generating the storage path of the current to-be-simulated layer data according to the pre-defined common path for storing the hidden layer data and thelayer identifier of the current to-be-simulated layer; performing simulation aiming at the current layer according to the data obtained from the file corresponding to the generated storage path; thehidden layer may comprise a plurality of layers; when simulation is carried out, storage paths of all hidden layer data do not need to be set independently, through the embodiment of the invention, the storage path of the current to-be-simulated layer data can be automatically generated, multi-layer continuous simulation is realized, the time for independently establishing simulation of each layeris saved, the simulation operation process is simplified, and the simulation efficiency is improved.

Description

Technical field [0001] The invention relates to the field of electronic technology, in particular to a neural network simulation method and device. Background technique [0002] In recent years, deep learning technology has developed rapidly. It has been widely used in solving advanced 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] For example, a neural network model trained in a GPU (Graphics Processing Unit, graphics processor) is used to perform image processing on personal computers, workstations, game consoles, and some mobile devices (such as tablets, smart phones, etc.). [0004] By transplanting the trained models in the computer or other processors to the chip, chip-level integration is realized to achieve wider applications, such as transplanting the neural network model in the...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06N3/063G06N3/08
Inventor 陈海波
Owner 深兰人工智能芯片研究院(江苏)有限公司
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