Macro Model of Advanced Devices for Parasitic Extraction
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abstract
2016 IEEE. In order to perform accurate parasitic extraction, foundries must provide the cross section profile of devices, and IP vendors must provide sufficient layout information. However, foundries and IP vendors are increasingly reluctant to reveal such sensitive information, especially for advanced devices. Therefore, the industry is faced with the following challenges: 1) foundries/IP vendors need to protect their trade secrets; 2) electronic design automation vendors need to integrate foundry data into extraction tools; and 3) IC designers need to have the accurate parasitic data. In this paper, we propose an innovative and practical solution to these challenges, by building a macro model around any region in 2-D/3-D on a circuit where foundries or IP vendors wish to hide information, yet the macro model allows accurate capacitance extraction inside and outside of the region. We first give algorithms to construct the macro model. Then, we describe how existing extraction algorithms can interface with the macro model to perform extraction for the entire circuit at the same accuracy as if complete information was given. The macro model can be used in finite difference method/finite element method and floating random walk, due to an equivalence theorem we proved. Finally, we propose the concept of equivalent profile and describe how to find one based on the macro model. Experimental results show the macro model can be efficiently constructed and used to produce accurate capacitance extraction.
