Fast and Accurate Current Prediction in Packages Using Neural Networks
Abstract
Electromigration (EM) has become one major reliability concern in modern integrated circuit packages. EM is
caused by large currents flowing in metals and the 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.
Research Areas
