SPIRAL: Signal-Power Integrity Co-Analysis for High-Speed Inter-Chiplet Serial Links Validation

Abstract

Chiplet has recently emerged as a promising solution to achieving further performance improvements by breaking down complex processors into modular components and communicating through high-speed inter-chiplet serial links. However, the ever-growing on-package routing density and data rates of such serial links inevitably lead to more complex and worse signal and power integrity issues than a large monolithic chip. This highly demands efficient analysis and validation tools to support robust design. In this paper, a signal-power integrity co-analysis framework for high-speed inter-chiplet serial links validation named SPIRAL is proposed. The framework first builds equivalent models for the links with a machine learning-based transmitter model and an impulse response based model for the channel and receiver: Then, the signal-power integrity is co-analyzed with a pulse response based method using the equivalent models. Experimental results show that SPIRAL yields eye diagrams with 0.82-1.85% mean relative error, while achieving $18-44 \times$ speedup compared to a commercial SPICE.