Semantic Embedding of Hardware Descriptions for Intelligent Clustering of Simulation Results in Chip Validation

Abstract

The escalating complexity of modern System-on-Chip (SoC) designs has demanded innovative methodologies for effective simulation analysis during the validation phase. Traditional analysis of simulation outputs suffers from poor scalability and limited automation, necessitating advanced techniques to streamline the validation effort. In this paper, we propose a novel framework leveraging semantic embedding of hardware descriptions to enable intelligent clustering of simulation results. We introduce embedding strategies based on natural language processing techniques, coupled with clustering algorithms, to intelligently group simulation outcomes. Extensive experiments validate the efficacy of our method, demonstrating improved debugging efficiency and reduced validation time.