基于网络布局规划算法的CC-ISA智能信息网络布线研究  

Cabling of CC-ISA intelligent information network based on network layout planning algorithm

作　　者：任亚西 REN Yaxi(Zhengzhou Technician College,Zhengzhou 450121,China)

机构地区：[1]郑州技师学院,郑州450121

出　　处：《自动化与仪器仪表》2024年第9期334-338,共5页Automation & Instrumentation

摘　　要：随着半导体芯片片上系统集成度的增加,对专用IP和的测试造成了一定的困难。针对这一问题,研究提出一种针对内部联合测试工作组测试网络的布局规划方法,以实现对其内部嵌入式仪器的控制访问。首先介绍了网络自身存在的特性约束,并提出使用模拟退火算法进行多目标优化问题的求解,为解决算法的局部最优问题,引入自适应因子对模型降温策略和劣解接收概率进行改进。最后研究对模型的算法和应用性能进行了实验分析,实验结果表明,算法的准确率和召回率分别为98.89%和99.01%,相对传统算法分别提升了16.62%和18.07%在模块数量为12和18个情况下,迭代次数相对降低了37.9%和43.9%。因此,研究提出的改进遗传退火算法,能够很好地实现网络模块的布局规划。The increase of system-on-chip integration makes it difficult to test dedicated IP and.Aiming at this problem,a layout planning method for the test network of the internal joint test working group is proposed to achieve control access to the embedded instruments.Firstly,the characteristic constraints of the network itself are introduced,and the simulated annealing algorithm is used to solve the multi-objective optimization problem.In order to solve the local optimal problem of the algorithm,the adaptive factor is introduced to improve the cooling strategy of the model and the receiving probability of the bad solution.The experimental results show that the accuracy rate and recall rate of the algorithm are 98.89%and 99.01%respectively,which is 16.62%and 18.07%higher than that of the traditional algorithm.When the number of modules is 12 and 18,the number of iterations is reduced by 37.9%and 43.9%.Therefore,the improved genetic annealing algorithm proposed in this paper can realize the layout planning of network modules well.

关 键 词：网络布局 模拟退火 特性约束 自适应 嵌入式仪器 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]