[1]聂 鑫,殷若兰,刘海峰.软硬件协同的遗传算法设计[J].计算机技术与发展,2021,31(11):114-121.[doi:10. 3969 / j. issn. 1673-629X. 2021. 11. 019]
　NIE Xin,YIN Ruo-lan,LIU Hai-feng.Design of Genetic Algorithm Based on Software and Hardware Cooperation[J].,2021,31(11):114-121.[doi:10. 3969 / j. issn. 1673-629X. 2021. 11. 019]
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软硬件协同的遗传算法设计()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
31
期数:
2021年11期
页码:
114-121
栏目:
系统工程
出版日期:
2021-11-10

文章信息/Info

Title:
Design of Genetic Algorithm Based on Software and Hardware Cooperation
文章编号:
1673-629X(2021)11-0114-08
作者:
聂 鑫1; 2 ; 殷若兰2 ; 刘海峰3
1. 智能机器人湖北省重点实验室,湖北 武汉 430205;
2. 武汉工程大学 计算机科学与工程学院,湖北 武汉 430205;
3. 华为技术有限公司,广东 深圳 518000
Author(s):
NIE Xin1; 2 ; YIN Ruo-lan2 ; LIU Hai-feng3
1. Hubei Key Laboratory of Intelligent Robot,Wuhan Institute of Technology,Wuhan 430205,China;
2. School of Computer Science and Engineering,Wuhan Institute of Technology,Wuhan 430205,China;
3. Huawei Technologies Co. ,Ltd. ,Shenzhen 518000,China
关键词:
遗传算法; FPGA; 软硬件协同; 软硬件划分; IP 核; 0-1 背包问题
Keywords:
genetic algorithm; FPGA; software and hardware cooperation; software and hardware division; IP core; 0-1 knapsack problem
分类号:
TP301
DOI:
10. 3969 / j. issn. 1673-629X. 2021. 11. 019
摘要:
针对软件和硬件实现方式各自的优点及不足,提出了遗传算法的软硬件协同设计方法,并且将这种方法在 FPGA上进行了具体的实现。 首先对遗传算法流程中的各个模块进行了详细的分析,根据软硬件的不同特点以及设计实现的目标,对遗传算法的功能模块进行了软硬件划分,然后对硬件实现的部分进行了详细的介绍,包括模块之间的连接,模块的内部状态机,模块的端口,所有硬件模块的功能仿真。 同时,为了保证软硬件之间的正常通讯,提出了一种新的软硬件交互通讯协议。 最后将硬件实现部分做成通用 IP 核,方便其他设计者使用,并给出了软硬件协同的遗传算法在二进制问题和 0-1 背包问题两个实例中的具体应用数据。 通过与纯软件实现方式的实验数据进行比较,提升了算法运行时间 50% 的效率,且算法的收敛性保持一致,进一步验证了该算法的适用性及高效性。
Abstract:
In view of the advantages and disadvantages of software and hardware implementation,a software hardware co-design method based on? ?genetic algorithm is proposed and implemented on FPGA. We analyze each module of the genetic algorithm flow chart,divide the function module of genetic algorithm in hardware and software according to their different features and design purpose. After that,we elaborate the implementation? of hardware part, including connection between modules, state machine in a module and interfaces of a module,function simulation of all hardware modules. We also provide a protocol to guarantee the communication between hardware and software. Ultimately,? ? ?the hardware implementation is designed as common IP kernel to be reused by other designers. Then we give the application data of software hardware cooperation genetic algorithm in binary problem and 0 -1 knapsack problem. Compared with the experimental data of pure software implementation mode,the efficiency of the algorithm running time is improved by 50% ,and the convergence of the algorithm is consistent,which further verifies the applicability and high efficiency of the algorithm.

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更新日期/Last Update: 2021-11-10