Algorithmic Tradeoff Exploration for Component Placement and Wire Routing in Nanomodular Electronics

2025-10-03

AI Summary

In nanoscale modular electronics (ME/NE) design automation, a fundamental trade-off exists between manufacturing time and bus length during component placement and routing. This work presents the first systematic exploration of this time–performance Pareto space, introducing an adaptive hierarchical algorithmic framework that integrates partitioning, floorplanning, stochasticity-aware component placement, and precise wire-printing–guided routing. The method explicitly accounts for the inherent randomness in micro/nanoscale deposition processes and supports dynamic reweighting of optimization objectives. Experimental results demonstrate that, with only a 21% increase in total wirelength, end-to-end fabrication time improves by up to 108×; alternatively, circuit performance can be prioritized without compromising manufacturability. This approach significantly enhances flexibility, scalability, and process–design co-optimization for heterogeneous nanocircuit synthesis.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search
• Machine Learning: Hardware-aware ML

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization

Abstract

Advances in fabrication technology have enabled modularizing electronic components at the micro- or nano-scale and composing these modules on demand into larger circuits. Micromodular and nanomodular electronics (ME and NE) open a new design space in electronics, promising a degree of flexibility, extensibility, and accessibility far superior to traditional monolithic methods. ME/NE leverage a multi-stage process of initial imprecise component deposition, followed by precise wire printing to compose them into a circuit. Due to imperfections in deposition, each circuit instance has a unique layout with its own component placement and wire routing solutions, putting the design automation process on the critical path. Moreover, high-performance nanomodular components enable the synthesis of larger heterogeneous circuits than traditional printed electronics, requiring more scalable algorithms. ME/NE thus introduce a tradeoff between the time-to-solution for placement/routing algorithms and the resulting total wire length, with the latter dictating circuit printing time. We explore this tradeoff by adapting standard partitioning, floorplanning, placement, and routing algorithms to the unique characteristics of ME/NE. Our evaluations demonstrate significant optimization headroom in different dimensions. For example, our tunable algorithms can deliver a $108 imes$ improvement in end-to-end manufacturing time at the cost of $21%$ increase in total wire length. Conversely, circuit quality/performance can be prioritized at the cost of increased manufacturing time, highlighting the value of the ability to dynamically navigate the tradeoff space according to the primary optimization metric.

Problem

• Explores tradeoffs between placement/routing time and wire length
• Adapts algorithms for nanomodular electronics' unique manufacturing process
• Enables tunable optimization between manufacturing speed and circuit quality

Innovation

• Adapting partitioning and floorplanning for nanomodular circuits
• Developing tunable placement and routing algorithms
• Exploring tradeoff between wire length and manufacturing time