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A Method for Finding Fragile Branches of FPGA Programs Based on Ant Colony Algorithm

A technology of ant colony algorithm and program, applied in calculation, calculation model, detection of faulty computer hardware, etc., can solve problems such as difficult evaluation of FPGA program reliability

Active Publication Date: 2018-09-28
XIDIAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0013] The purpose of the invention is to overcome the difficult problem of evaluating FPGA program reliability in the prior art

Method used

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  • A Method for Finding Fragile Branches of FPGA Programs Based on Ant Colony Algorithm
  • A Method for Finding Fragile Branches of FPGA Programs Based on Ant Colony Algorithm
  • A Method for Finding Fragile Branches of FPGA Programs Based on Ant Colony Algorithm

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Experimental program
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Embodiment 1

[0073] In VHDL, in the hierarchical relationship of modules, the bottom entity (module) is the most basic functional module, and the so-called topological connection refers to the port connection relationship between these basic functional modules. The port connections of modules (components) are defined in the upper modules that call these components. Only by finding out the module calling relationship in the complete VHDL program can the port connection relationship between the basic function modules be determined.

[0074] VHDL is a hardware description language with a strict grammatical structure. According to the grammatical structure, we can use fixed keywords to find statements describing the topological connection relationship: entity definition statement, port declaration statement, component instantiation statement and port mapping statement. The entity definition statement contains the name information of the entity. Since the VHDL language is written in units of en...

Embodiment 2

[0132] On the basis of Embodiment 1, further, the engineering code is tested, and its implementation process includes the following steps:

[0133] (1) read in the FPGA program; input the FPGA program into the execution program;

[0134] (2) determine the module number; In the present embodiment, through program detection, the module number that the FPGA program of input comprises is 8;

[0135] (3) Locate to the beginning of the module; through the search mode, find the enlightenment module of 8 modules;

[0136] (4) Use the port keyword to determine the port of each module, and record the port name and port quantity. The test structure is shown in the following table:

[0137]

[0138] (5) Use the component keyword to determine the component, and record the name of the component, the port name and quantity of the component;

[0139] (6) Use the port map keyword to determine the connection relationship of the components;

[0140] (7) Repeat (4)~(6) until every module is...

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Abstract

The invention belongs to the technical field of electronic circuits, and particularly relates to an FPGA program fragile branch obtaining method based on the ant colony optimization. The method comprises the steps of searching for the topology connecting relation of an FPGA program, building a model, and conducting shortest path judgment by means of the ant colony optimization. In this way, the branch with the highest error rate can be obtained according to the flow topology relation between signals of different FPGA modules after modeling is conducted based on ant colony behavioral characteristics, and then a basis is provided for evaluating the reliability of the FPGA program.

Description

technical field [0001] The invention belongs to the technical field of electronic circuits, and in particular relates to a method for obtaining fragile branches of FPGA programs based on an ant colony algorithm. Background technique [0002] Ant colony optimization (ACO), also known as ant algorithm, is a probabilistic algorithm used to find an optimal path in a graph. It was proposed by Marco Dorigo in his doctoral dissertation in 1992 and was inspired by the behavior of ants in finding paths in the search for food. Ant colony algorithm is a simulated evolutionary algorithm, preliminary research shows that the algorithm has many excellent properties. Ant colony algorithm has the validity and application value of a new simulated evolutionary optimization method. [0003] The characteristics of ant colony algorithm: [0004] 1) Ant colony algorithm is a self-organizing algorithm. In system theory, self-organization and other organizations are two basic classifications of ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F11/22G06N3/00
Inventor 闫允一李海旭郭宝龙
Owner XIDIAN UNIV