Optimising topographical pillar placement for thermal heat distribution with Artificial Intelligence

Abstract

The increased heat on an integrated circuit is a limiting factor for the performance and lifetime of a chip. The increased power density on chips resulted in increased heat and the formation of non-uniform hotspots. Earlier research has shown that the package design and layout of package components in flip-chip design can influence the thermal heat distribution on a chip. Especially the copper pillars play a role in the distribution of heat on a chip. These pillars can reduce the maximal temperature of a hotspot when placed correctly. Designing a pillarmap that adheres to manufacturing rules can be lengthy and complex. Therefore, pillarmaps are currently not optimised for thermal behaviour. The default strategy is to place them in a grid. This research aims to automatically optimise pillarmaps for thermal heat distribution with the use of artificial intelligence. Pillarmaps are optimised using the theoretical behaviour of heat in packages combined with Stochastic Hill Climbing and Squeaky Wheel Optimisation techniques. The layouts are automatically re-simulated in a finite elements simulation tool when needed. The optimisation strategies are tested on experimental setups with single and dual hotspots. The optimisation strategies are also evaluated on an actual product, but limitations on pillar placement reduced the effect of the optimisation techniques. Also, the influence of different pillar diameters on an optimisation strategy is discussed. The optimisation techniques can reduce hotspots and improve the heat distribution in a scenario with multiple hotspots. The success of the optimisation techniques is subject to the amount of freedom they have to change pillar locations and where the hotspots are on the chip.