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Method for realizing that nGraph framework supports FPGA rear-end equipment

A technology of back-end equipment and framework, applied in the field of super-heterogeneous acceleration for deep learning model training

Pending Publication Date: 2020-11-27
LANGCHAO ELECTRONIC INFORMATION IND CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the current nGraph framework does not support FPGA back-end devices. Given that FPGA has the characteristics of low power consumption, programmable, and highly parallel, if the nGraph framework can support FPGA back-end devices, it will undoubtedly improve the training performance of deep learning neural networks. Can provide great help to further enhance

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  • Method for realizing that nGraph framework supports FPGA rear-end equipment
  • Method for realizing that nGraph framework supports FPGA rear-end equipment
  • Method for realizing that nGraph framework supports FPGA rear-end equipment

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Embodiment Construction

[0056] The core of this application is to provide a method for implementing the nGraph framework to support FPGA back-end devices, enabling the nGraph framework to support FPGA back-end devices, so as to further realize the training or inference process of the deep learning neural network computation graph constructed by the user based on the nGraph framework Deploy to FPGA back-end devices for acceleration purposes. Another core of the present application is to provide an apparatus and device for implementing an nGraph framework to support FPGA back-end devices, and an nGraph framework for supporting FPGA back-end devices, which also have the above technical effects.

[0057] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present app...

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Abstract

The invention discloses a method for realizing an nGraph framework to support FPGA rear-end equipment and a related device. The method comprises that: an OpenCL standard API library is integrated intothe nGraph framework; an FPGA rear-end equipment creation module used for registering FPGA rear-end equipment, initializing an OpenCL environment and obtaining the FPGA rear-end equipment is createdin the nGraph framework; an FPGA cache space processing module used for opening up an FPGA cache space and reading and writing an FPGA cache is created in the nGraph framework; an OP kernel implementation module is created in the nGraph framework, wherein the OP kernel implementation module is used for creating an OP kernel and compiling the OP kernel; and an FPGA compiling execution module used for registering, scheduling and executing the OP kernel is created in the nGraph framework. According to the method, the nGraph framework can support the FPGA rear-end equipment.

Description

technical field [0001] The present application relates to the technical field of deep learning model training super-heterogeneous acceleration, and in particular, to a method for implementing nGraph framework to support FPGA back-end equipment; it also relates to a device and device for implementing nGraph framework to support FPGA back-end equipment, and a method for supporting FPGA back-end equipment nGraph framework for backend devices. Background technique [0002] At present, DNN (Deep Neural Network, deep neural network) has obtained a wide range of applications, including image and video classification, speech recognition and language translation. However, as deep neural networks are more widely developed and used, the model size becomes larger and larger, for example, up to hundreds of layers, with a total of 10 million to 20 million parameters. This growth makes efficient model training even more important. The emergence of deep learning frameworks such as Tensorf...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/08G06N3/04G06N3/063
CPCG06N3/082G06N3/063G06N3/045G06F8/41G06N3/10G06F30/34G06F30/27G06F8/451G06F9/547
Inventor 曹芳郭振华王丽高开
Owner LANGCHAO ELECTRONIC INFORMATION IND CO LTD