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Neural network interaction system and method based on AXI-APB, server and storage medium

A neural network and interactive system technology, applied in the field of AXI-APB-based neural network interactive system, can solve problems such as inability to realize conversion and access

Active Publication Date: 2020-04-28
SHENZHEN CORERAIN TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, the current APB and AXI interconnection network cannot realize the interface conversion and access of any number of AXI master devices to an APB or AXI slave device, and cannot flexibly realize cross-clock domain and high-frequency requirements according to actual needs

Method used

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  • Neural network interaction system and method based on AXI-APB, server and storage medium
  • Neural network interaction system and method based on AXI-APB, server and storage medium
  • Neural network interaction system and method based on AXI-APB, server and storage medium

Examples

Experimental program
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Embodiment 1

[0045] figure 1 A schematic structural diagram of an AXI-APB-based neural network interaction system provided by Embodiment 1 of the present invention. Such as figure 1 As shown, the AXI-APB-based neural network interaction system 100 includes a sending module 110 and a feedback module 120, and the sending module 110 includes a receiving unit 111, a conversion unit 112, an analysis unit 113, an arbitration unit 114 and an execution unit 115:

[0046] The receiving unit 111 is configured to receive a plurality of first excitation signals sent by a plurality of master devices, and the first excitation signals follow the AXI communication protocol;

[0047]Specifically, the excitation signal refers to an input signal, which mainly works by reducing the frequency of the square wave and superimposing the voltage. In sequential logic circuits, it is also called the internal output signal of the combinational circuit. The AXI communication protocol refers to a bus protocol, which ...

Embodiment 2

[0060] Embodiment 2 of the present invention is further optimized on the basis of Embodiment 1. figure 2 A schematic structural diagram of an AXI-APB-based neural network interaction system provided by Embodiment 2 of the present invention. Such as figure 2 As shown, the AXI-APB-based neural network interaction system 200 of this embodiment includes a sending module 210 and a feedback module 220, and the sending module includes a receiving unit 211, a conversion unit 212, an analysis unit 213, an arbitration unit 214 and an execution unit 215:

[0061] The receiving unit 211 is configured to receive a plurality of first excitation signals sent by a plurality of master devices, and the first excitation signals follow the AXI communication protocol;

[0062] Specifically, the excitation signal refers to an input signal, which mainly works by reducing the frequency of the square wave and superimposing the voltage. In sequential logic circuits, it is also called the internal ...

Embodiment 3

[0091] image 3 It is a flowchart of an AXI-APB-based neural network interaction method provided by Embodiment 3 of the present invention. Such as image 3 As shown, a neural network interaction method based on AXI-APB, including:

[0092] Step S310, receiving multiple first excitation signals sent by multiple master devices, the first excitation signals complying with the AXI communication protocol;

[0093] Specifically, the excitation signal refers to an input signal, which mainly works by reducing the frequency of the square wave and superimposing the voltage. In sequential logic circuits, it is also called the internal output signal of the combinational circuit. The AXI communication protocol refers to a bus protocol, which is the most important part of AMBA3.0 proposed by ARM, and is an on-chip bus for high performance, high bandwidth, and low delay.

[0094] Step S320, converting the first excitation signal into a second excitation signal according to the first conv...

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Abstract

The invention discloses a neural network interaction system and method based on AXI-APB, a server and a storage medium, and the system comprises the following parts: a receiving unit which is used forreceiving a plurality of first excitation signals transmitted by a plurality of pieces of main equipment; a conversion unit that is used for converting the first excitation signal into a second excitation signal according to the first conversion bridge; an analysis unit that is used for analyzing the plurality of second excitation signals according to a first preset channel and the plurality of APB interfaces so as to obtain a plurality of pieces of first identification information corresponding to the plurality of second excitation signals; an arbitration unit that is used for determining the priority of each corresponding second excitation signal according to the plurality of pieces of first identification information; an execution unit that is used for executing a plurality of corresponding second excitation signals according to the priorities; and a feedback module that is used for feeding back the execution result to the corresponding main equipment. According to the invention, through AXI-APB conversion, a plurality of AXI master devices are supported to access one APB slave device through a fixed-point computing rotation training arbitration method, and clock domain crossing and high-frequency requirements are flexibly met according to actual requirements.

Description

technical field [0001] Embodiments of the present invention relate to neural network data transmission technology, and in particular to an AXI-APB-based neural network interaction system, method, server and storage medium. Background technique [0002] With the continuous development of science and technology in recent years, in order to ensure the high performance requirements of information systems, more computing engines and storage devices are often included. After using multiple computing engines and storage units, there are multiple ways of access and modes and multiple ports, which leads to isolation between interfaces, so it is necessary to implement interface conversion and access between multiple modules. Due to application requirements, different modules require different timings. The connection between modules requires not only interface conversion, but also cross-clock domain and high clock frequency requirements between clocks. After adopting the APB and AXI i...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/063H04L29/06
CPCG06N3/063H04L69/08Y02D10/00
Inventor 徐欣李远超蔡权雄牛昕宇
Owner SHENZHEN CORERAIN TECH CO LTD
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