GPU-Accelerated Effective Resistance Analysis for 3D IC Power Delivery Network

2026-07-07

AI Summary

This work addresses the non-uniform effective resistance distribution and severe IR drop in 3D IC power delivery networks caused by suboptimal through-silicon via (TSV) placement. To enable rapid assessment of TSV layout impact on power integrity during early design stages, the authors propose a GPU-accelerated effective resistance analysis framework. Leveraging highly efficient GPU-parallelized numerical solvers as a replacement for conventional direct solvers, the method achieves a speedup of five to six orders of magnitude while maintaining exceptionally low maximum and average relative errors. Compared to traditional approaches, the proposed framework enhances analysis throughput by 10⁵–10⁶ times without compromising accuracy, thereby significantly improving the efficiency and scalability of early-stage verification for complex 3D IC power networks.

Abstract

Three-dimensional (3D) integration is a critical technique for enhancing transistor density, improving power efficiency, and reducing interconnect delays. However, as current demands and design complexity increase, power deliver networks (PDNs) are facing growing challenges.Careful planning of through-silicon vias (TSVs) is essential for ensuring reliable PDNs, where effective resistance serves as a vital metric for the reliability. Ill-planned TSVs often cause 3D IC with unevenly distributed effective resistance and consequently severer IR Drop.In this paper, we propose a GPU-accelerated framework on accurate effective resistance analysis for early stage 3D IC PDNs. The proposed framework achieves a speedup of 5 to 6 orders of magnitude compared to the conventional direct solver, while maintaining negligible deviations in both maximum and average relative errors.

Problem

• 3D IC
• Power Delivery Network
• Effective Resistance
• TSV
• IR Drop

Innovation

• GPU acceleration
• effective resistance
• 3D IC
• power delivery network
• through-silicon via