This paper presents fast and automated electromigration (EM) reliability modeling by using automated modeling generation (AMG) algorithm. The AMG converts human based EM modeling into an automated modeling and simulation process with the help of ANSYS parametric design language (APDL) program. For automating the neural model training process, training-driven adaptive sampling is applied to integrate data generation, data distributions determination, model structure adaptation, training and testing into a unified framework. Fully automated reliability model construction and simulation is achieved for the first time. This method effectively shortens the period of EM modeling by using dynamic sampling method. Furthermore, the heat generation from active devices has been considered to describe the heat effect on the interconnect reliability. Through the proposed technique, the allowable sizes, temperature and output power of a CMOS radio frequency power amplifier (RF PA) are derived to give reliability criteria for PA designer.

Additional Metadata
Keywords Automated model generation, CMOS power amplifier, Heat generation, Interconnect reliability, Neural networks
Persistent URL dx.doi.org/10.1007/s10836-016-5639-4
Journal Journal of Electronic Testing: Theory and Applications (JETTA)
Citation
Gu, J. (Junjie), Fu, H. (Haipeng), Na, W. (Weicong), Zhang, Q.J, & Ma, J. (Jianguo). (2017). Fast and Automated Electromigration Analysis for CMOS RF PA Design. Journal of Electronic Testing: Theory and Applications (JETTA), 33(1), 133–140. doi:10.1007/s10836-016-5639-4