Interconnect reliability analysis of ULSI using automated model generation algorithm. Issue 6 (17th March 2016)

• Record Type: Journal Article
• Authors: Lin, Qian; Fu, Haipeng; Na, Weicong; He, Feifei; Li, Xi; Cheng, Qianfu; Zhu, Yuanyuan
• Is Part Of: International journal of RF and microwave computer-aided engineering. Volume 26:Issue 6(2016)
• Page Start: 481
• Page End: 488
• Publication Date: 2016-03-17
• Subjects: interconnect reliability -- automated model generation -- interpolation technique -- annual neural network; Microwave devices -- Computer-aided design -- Periodicals; Computer-aided engineering -- Periodicals; 621.3813
• DOI: 10.1002/mmce.20992
• Languages: English
• ISSNs: 1096-4290

Abstract

ABSTRACT: Fast interconnect reliability analysis is needed with the rapid development of ULSI (Ultra Large Scale Integration). Therefore, we aims to use the automated model generation (AMG) algorithm to analyze the ULSI reliability of metal interconnects. This is the first time to use the AMG algorithm in the field of IC reliability analysis. The AMG algorithm can achieve data generation automatically, determination of data distribution, adaptation of model structure, model training and testing. Using AMG algorithm in the reliability analysis, the number of the training data can be reduced by the adaptive sampling process and the incorporation of interpolation technique. This method can greatly improve the efficiency of the simulation and shorten the time for modeling than the existing manual neural network modeling methods. In this paper, we takes a power amplifier for example to validate the advantage of this technique. © 2016 Wiley Periodicals, Inc. Int J RF and Microwave CAE 26:481–488, 2016.