Open-Source Autonomous VLSI Design Tools: A Review

Abstract

The evolution of Very Large Scale Integration (VLSI) design has witnessed a paradigm shift with the advent of autonomous and open-source tools. Traditionally, VLSI design relied on proprietary Electronic Design Automation (EDA) tools, which were expensive and limited in flexibility. The emergence of open-source autonomous design tools has democratized chip design, providing accessible, customizable, and intelligent solutions. This paper reviews the current state of open-source autonomous VLSI design tools, discussing their architectures, capabilities, and the integration of Artificial Intelligence (AI) and Machine Learning (ML) for tasks such as placement, routing, power optimization, and verification. Key challenges, limitations, and potential research directions are also explored. The review aims to provide a comprehensive guide for researchers, educators, and industry practitioners interested in adopting open-source autonomous approaches for VLSI design.

KEYWORDS: VLSI, EDA, Open-source, Autonomous Design, AI, Machine Learning, Placement, Routing, Verification