摘要
为了优化测试时间,提高片上网络(NoC)资源内核的测试效率,结合NoC测试特点,提出一种基于超立方体拓扑结构的NoC测试规划优化方法。该方法针对超立方体结构自身优势设计一种具有部分自适应能力的E-cube路由算法,增加测试过程中对路由节点和通信链路的利用率;通过引入混度序列和压缩因子对粒子算法进行改进,增加种群多样性。在ITC’02国际标准电路测试集上进行对比实验,结果表明,与其他方法相比,该方法测试时间最大优化率可达17.38%,有效缩短了测试时间。
In order to optimize the test time and improve the test efficiency of the NoC resource core, combining the characteristics of NoC testing, we propose a method of NoC test planning optimization based on the hypercube topology. Aiming at the advantages of hypercube structure, this method designed an E-cube routing algorithm with partial adaptive ability, which increased the utilization ratio of routing nodes and communication links in the test process. The particle algorithm was improved by introducing mixing sequence and compression factor to increase population diversity. A comparison experiment was performed on the ITC’02 international standard circuit test set. The results show that the proposed method has a maximum test time optimization rate of 17.38% compared with other methods, which effectively shortens the test time.
作者
胡聪
信文雪
周甜
朱爱军
许川佩
Hu Cong;Xin Wenxue;Zhou Tian;Zhu Aijun;Xu Chuanpei(School of Electronic Engineering and Automation,Guilin University of Electronic Technology,Guilin 541004,Guangxi,China;School of Electronic Information and Automation,Guilin University of Aerospace Technology,Guilin 541004,Guangxi,China;Guangxi Key Laboratory of Automatic Detection Technology and Instruments,Guilin 541004,Guangxi,China)
出处
《计算机应用与软件》
北大核心
2022年第4期75-79,共5页
Computer Applications and Software
基金
国家自然科学基金项目(61861012,61561012)
广西自然科学基金项目(2018GXNSFAA138115,2017GXNSFAA198021)
广西自动检测技术与仪器重点实验室(YQ18109)。
关键词
片上网络
超立方体拓扑结构
测试优化
改进粒子群算法
Network-on-chip
Hypercube topology
Test optimization
Improved particle swarm optimization algorithm