Two-dimensional directed self-assembly (2D-DSA) is an emerging lithography technology for advanced process nodes. We can determine the orientations of double posts to guide block copolymers to form feasible 2D guiding template patterns by the 2D-DSA process. This paper presents the first work to handle the 2D-DSA simultaneous placement and routing problem. We first propose a novel graph to model feasible guiding templates with a constant-time update scheme for each double-post assignment. Based on a graph model, we then present an algorithm for 2D-DSA simultaneous placement and routing, with a broadcast-based cost function for 2D-DSA cell placement and a graph-based scheme for DSA-compliant routing. Finally, we employ a strongly effective region property to minimize the cuts in the final layout. Experimental results show that our algorithm can efficiently generate a 2D-DSA placement and routing solution with high routability and a low cut number.

2023 ICCAD CAD Contest Problem B is an extended problem from 2022 ICCAD CAD Contest Problem B [1]–[2] for addressing more complex real world 3D implementation constraints. In the chiplet era, the benefits from multiple factors can be observed by splitting a large single die into multiple small, chiplet, dies. By having the multiple small, chiplet, dies with die-to-die (D2D) vertical connections, the benefits including: 1) better yield, 2) better timing/performance, 3) better cost, and 4) faster time-to-market. How to do the netlist partitioning, cell placement for both the standard cells and the macros in each of the chiplet dies, and nevertheless how to determine the location of the D2D inter-connection terminals becomes a new topic. To address this chiplet era physical implementation problem, ICCAD-2023 contest encourages the research in the techniques of multi-die netlist partitioning and placement of both standard cells and macros with D2D vertical connections. We provided (i) a set of benchmarks and (ii) an evaluation metric of multiple objectives that facilitate contestants to develop, test, and evaluate their new algorithms.