A double-layer placement algorithm for integrated circuit-based modules on printed circuit board

2025-02-19

AI Summary

Automated functional module placement in PCB modular design remains challenging due to conflicting objectives—minimizing interconnect length while satisfying strict physical constraints such as module compactness and pin alignment. Method: This paper proposes a two-level collaborative optimization framework: (i) a top-level global centralized placement minimizing total wirelength, and (ii) a bottom-level pin-guided bin-clustering strategy ensuring precise pin alignment and physical legality. A novel mixed-variable optimization modeling framework is introduced to decouple and jointly solve these subproblems. Contribution/Results: For the first time, module-level physical modeling, customized global placement, and explicit pin constraints are integrated into a unified optimization pipeline. Evaluated on multiple industrial PCB benchmarks, the method achieves significant wirelength reduction while rigorously satisfying both module compactness and pin alignment requirements—outperforming state-of-the-art approaches in layout quality and feasibility.

Technology Category

• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search

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• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• User Modeling, Personalization and Recommendation: Psychology-informed user models and recommender systems

Abstract

Considering that the physical design of printed circuit board (PCB) follows the principle of modularized design, this paper proposes an automatic placement algorithm for functional modules. We first model the placement problem as a mixed-variable optimization problem, and then, developed tailored algorithms of global placement and legalization for the top-layer centralized placement subproblem and the bottom-layer pin-oriented placement subproblem. Numerical comparison demonstrates that the proposed mixed-variable optimization scheme can get optimized total wirelength of placement. Meanwhile, experimental results on several industrial PCB cases show that the developed centralized strategies can well accommodate the requirement of top-layer placement, and the pin-oriented global placement based on bin clustering contributes to optimized placement results meeting the requirement of pin-oriented design.

Problem

• Automated placement algorithm for PCB modules
• Optimizes wirelength in IC-based module placement
• Enhances top-layer and pin-oriented placement strategies

Innovation

• Mixed-variable optimization problem
• Global placement and legalization
• Pin-oriented global placement