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Publications of SPCL

P. Iff, B. Bruggmann, M. Besta, L. Benini, T. Hoefler:
	PlaceIT: Placement-based Inter-Chiplet Interconnect Topologies (Feb. 2025) Abstract 2.5D integration technology is gaining traction as it copes with the exponentially growing design cost of modern integrated circuits. A crucial part of a 2.5D stacked chip is a low-latency and high-throughput inter-chiplet interconnect (ICI). Two major factors affecting the latency and throughput are the topology of links between chiplets and the chiplet placement. In this work, we present PlaceIT, a novel methodology to jointly optimize the ICI topology and the chiplet placement. While state-of-the-art methods optimize the chiplet placement for a predetermined ICI topology, or they select one topology out of a set of candidates, we generate a completely new topology for each placement. Our process of inferring placement-based ICI topologies connects chiplets that are in close proximity to each other, making it particularly attractive for chips with silicon bridges or passive silicon interposers with severely limited link lengths. We provide an open-source implementation of our method that optimizes the placement of homogeneously or heterogeneously shaped chiplets and the ICI topology connecting them for a user-defined mix of four different traffic types. We evaluate our methodology using synthetic traffic and traces, and we compare our results to a 2D mesh baseline. PlaceIT reduces the latency of synthetic L1-to-L2 and L2-to-memory traffic, the two most important types for cache coherency traffic, by up to 28% and 62%, respectively. It also achieve an average packet latency reduction of up to 18% on traffic traces. PlaceIT enables the construction of 2.5D stacked chips with low-latency ICIs. Documents download article: access preprint on arxiv: download slides:
	BibTeX
@article{,   author={Patrick Iff and Benigna Bruggmann and Maciej Besta and Luca Benini and Torsten Hoefler},   title={{PlaceIT: Placement-based Inter-Chiplet Interconnect Topologies}},   year={2025},   month={02},   doi={10.48550/arXiv.2502.01449}, }