Method for realizing neural network model splitting by using multi-core processor, and related product

A neural network model, multi-core processor technology, applied in the field of deep learning

Active Publication Date: 2020-02-21
ANHUI CAMBRICON INFORMATION TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Traditional data parallel solutions cannot meet the requirements...

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  • Method for realizing neural network model splitting by using multi-core processor, and related product
  • Method for realizing neural network model splitting by using multi-core processor, and related product
  • Method for realizing neural network model splitting by using multi-core processor, and related product

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[0061] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0062] It should be understood that the terms "first", "second" and "third" in the claims, specification and drawings of the present disclosure are used to distinguish different objects, rather than to describe a specific order. The terms "comprising" and "comprises" used in the specification and claims of this disclosure indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude one or more other features, integers , steps, operations, elements, components, and / or the presence or addition of collections thereof.

[0063] It should also be understood that the terminology used in this disclosure is for the purpose of describing particular embodiments only, and is not intended to limit the present disclosure. As used in this disclosure a...

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Abstract

The embodiment of the invention discloses a method for realizing neural network model splitting by using a multi-core processor, and a related product. When operators capable of being split exist in the neural network model, the operators are split, an optimal splitting combination is selected to obtain the optimal splitting result of the whole neural network model, then the sub-operators corresponding to the optimal splitting result are executed in parallel through multiple cores, and the purpose of reducing resource consumption of computer equipment is achieved.

Description

technical field [0001] The invention relates to the technical field of deep learning, in particular to a method for splitting a neural network model with a multi-core processor and related products. Background technique [0002] In recent years, neural network processors have been continuously proposed, and like general-purpose processors, they are expanding from single-core to multi-core. This expanded multi-core structure can support data parallelism in the training phase to improve data throughput and speed up training. However, in the inference stage, the end-to-end delay of the deep neural network is higher than that of the throughput, which often determines the availability of the accelerator in a certain scenario. Traditional data parallel solutions cannot meet the requirements of small data and low latency for accelerators in inference scenarios. Contents of the invention [0003] In order to solve the above-mentioned technical problems, the embodiment of the pre...

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Application Information

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IPC IPC(8): G06N3/063G06F15/163
CPCG06N3/063G06F15/163
Inventor 不公告发明人
Owner ANHUI CAMBRICON INFORMATION TECH CO LTD
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