Generative AI and Large Language Models for Hardware Design

Abstract

The rapid evolution of Generative Artificial Intelligence (AI) and Large Language Models (LLMs) has opened new opportunities in the field of hardware design. Traditionally, hardware design has relied on rule-based and simulation-driven approaches, which are often time-consuming and resource intensive. This paper reviews the application of generative AI and LLMs in hardware design, focusing on their potential to accelerate circuit synthesis, verification, layout optimization, and fault detection. We discuss state-of-the art AI models, key challenges, and integration strategies for enhancing design efficiency. A comparative analysis is provided between traditional design methods and AI-assisted approaches. Finally, the paper presents insights into future directions, highlighting how AI can transform hardware development pipelines in both academic and industrial settings.

KEYWORDS: Generative AI, Large Language Models, Hardware Design, Circuit Synthesis, Verification, Layout Optimization, Fault Detection