| Autor: |
Tianjian Lu, Jian-Ming Jin, Yanan Liu, Ken Wu, Jin Y. Kim |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
2019 IEEE International Symposium on Electromagnetic Compatibility, Signal & Power Integrity (EMC+SIPI). |
| DOI: |
10.1109/isemc.2019.8825314 |
| Popis: |
Electromigration (EM) has become one major reliability concern in modern integrated circuit (IC) packages. EM is caused by large currents flowing in metals and the resulting mean time to failure (MTTF) is highly dependent on the maximum current value. We here propose a scheme for fast and accurate prediction of the maximum current on the ball grid arrays (BGAs) in a package given the pin current information of the die. The proposed scheme uses neural networks to learn the resistance network of the package and achieve the non-linear current mapping. The fast prediction tool can be used for analysis and design exploration of the pin assignment on the die level. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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