GATMesh: Clock Mesh Timing Analysis using Graph Neural Networks

📝 Original Info

• Title: GATMesh: Clock Mesh Timing Analysis using Graph Neural Networks
• ArXiv ID: 2507.05681
• Date: 2025-07-08
• Authors: 제공된 정보에 저자 명단이 포함되어 있지 않습니다.

📝 Abstract

Clock meshes are essential in high-performance VLSI systems for minimizing skew and handling PVT variations, but analyzing them is difficult due to reconvergent paths, multi-source driving, and input mesh buffer skew. SPICE simulations are accurate but slow; yet simplified models miss key effects like slew and input skew. We propose GATMesh, a Graph Neural Network (GNN)-based framework that models the clock mesh as a graph with augmented structural and physical features. Trained on SPICE data, GATMesh achieves high accuracy with average delay error of 5.27ps on unseen benchmarks, while achieving speed-ups of 47146x over multi-threaded SPICE simulation.

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