Analytical Heterogeneous Die-to-Die 3D Placement with Macros
<|reference_start|>Analytical Heterogeneous Die-to-Die 3D Placement with Macros: This paper presents an innovative approach to 3D mixed-size placement in heterogeneous face-to-face (F2F) bonded 3D ICs. We propose an analytical framework that utilizes a dedicated density model and a bistratal wirelength model, effectively handling macros and standard cells in a 3D solution space. A novel 3D preconditioner is developed to resolve the topological and physical gap between macros and standard cells. Additionally, we propose a mixed-integer linear programming (MILP) formulation for macro rotation to optimize wirelength. Our framework is implemented with full-scale GPU acceleration, leveraging an adaptive 3D density accumulation algorithm and an incremental wirelength gradient algorithm. Experimental results on ICCAD 2023 contest benchmarks demonstrate that our framework can achieve 5.9% quality score improvement compared to the first-place winner with 4.0x runtime speedup. Additional experiments on modern RISC-V designs further validate the generalizability and superiority of our framework.<|reference_end|>
@article{zhao2024analytical,
    title={Analytical Heterogeneous Die-to-Die 3D Placement with Macros},
    author={Yuxuan Zhao, Peiyu Liao, Siting Liu, Jiaxi Jiang, Yibo Lin, Bei Yu},
    journal={arXiv preprint arXiv:2403.09070},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.09070},
    primaryClass={cs.AR}
}