融合哈希编码及分块策略的双自编码器电路可靠性预测  

Circuit Reliability Prediction Based on Dual Autoencoders Combining Hash Coding and Partitioning Strategy

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作  者:黄抒意 黄正峰 施莹 楼俊钢[1,2] Huang Shuyi;Huang Zhengfeng;Shi Ying;Lou Jungang(Key Laboratory of Smart Management&Application of Modern Agricultural Resources,Huzhou University,Huzhou 313000;School of Information Engineering,Huzhou University,Huzhou 313000;School of Microelectronics,Hefei University of Technology,Hefei 230601;School of Science and Engineering,Huzhou College,Huzhou 313000)

机构地区:[1]湖州师范学院现代农业资源智慧管理与应用研究重点实验室,湖州313000 [2]湖州师范学院信息工程学院,湖州313000 [3]合肥工业大学微电子学院,合肥230601 [4]湖州学院理工学院,湖州313000

出  处:《计算机辅助设计与图形学学报》2022年第4期552-562,共11页Journal of Computer-Aided Design & Computer Graphics

基  金:国家自然科学基金(61772199,61802123);浙江省自然科学基金(LR20F020002)。

摘  要:为实现门级电路可靠性的快速评估,提出一种融合哈希编码和分块策略的双自编码器电路可靠性评估方法.首先分析并提取与门级电路可靠性相关的主要特征,构建面向电路可靠性评估的特征数据集;然后针对电路输入向量不定长、量纲不同等难点,提出一种融合CRC20哈希算法和分块策略的电路输入向量特征标准化方法;再采用不同激活函数的栈式自编码器学习数据不同特征,建立双自编码器模型.在74系列、ISCAS85和EPFL等不同规模电路上的实验结果表明,在不同网络层数情况下,哈希融合分块策略的预测性能可以提升1.79%~8.29%,而双自编码器模型相较于基准模型的预测性能可以提升21.10%~47.08%.For fast prediction of gate-level circuit reliability,a method based on dual-autoencoder combining Hash coding and partitioning strategy is proposed.Firstly,the main characteristics related to gate-level circuit reliability are analyzed and extracted,and a feature data set for circuit reliability prediction is constructed.Next,facing the difficulties of circuit input vector with variable length and different dimensions,a characteristic standardization method for circuit input vector based on Hash coding and partitioning strategy is proposed.Then stacked autoencoders are used with different activation functions to learn different characteristics of data and establish a dual-autoencoder model.The experimental results on circuits of different scales such as 74 series,ISCAS85 and EPFL show that the proposed characteristic standardization method can improve 1.79%-8.29%prediction performance under the condition of different network layers,and the dual-autoencoder model can improve the prediction performance by 21.10%-47.08%compared with the benchmark model.

关 键 词:电路可靠性 自编码器 CRC哈希 

分 类 号:TP391.41[自动化与计算机技术—计算机应用技术]

 

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