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arXiv · 2502.10932

Simultaneous Multi-die Floorplanning and Technology Assignment

Cristhian Roman-Vicharra·Prianka Sengupta·Runzhi Wang·Yiran Chen·Jiang Hu
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Abstract

In heterogeneous integration, different dies may employ distinct technologies, making floorplanning across multiple dies inherently coupled with technology assignment. By assuming a fixed technology, almost all prior floorplanning studies were developed without addressing the challenge of technology assignment. This work presents the first systematic study of multi-die floorplanning that treats technology choice as a variable. To address the challenge of variable block areas, we incorporate a recent machine learning technique for rapid PPA estimation. Our methods jointly optimize area, wirelength, performance, power, and cost, thereby highlighting the importance of technology assignment. Experimental evaluations, validated with a commercial tool for both 2.5D and 3D ICs, demonstrate that our systematic optimizations significantly outperform a greedy approach.

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Cristhian Roman-Vicharra, Prianka Sengupta, Runzhi Wang, Yiran Chen, Jiang Hu. 2025-02-15. Simultaneous Multi-die Floorplanning and Technology Assignment. https://arxiv.org/abs/2502.10932

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