CHIA: An open-source framework for principled, agentic AI-driven hardware/software co-design research

Problem: Existing AI-driven hardware/software co-design research is limited to isolated, small-scale demonstrations due to the difficulty of designing and deploying complex AI-infused workflows. Method: CHIA introduces an open-source framework that models agentic AI-driven co-design flows as directed cyclic graphs (CHIA loops) with node implementations for tools like Chipyard, gem5, and Vivado, and provides features for isolation, profiling, and fault-tolerant execution. Finding: Five case studies demonstrate CHIA's capability, including automatic RTL-to-gem5 alignment, LLM-driven RTL microarchitecture implementation, and evolutionary architectural discovery. Why it matters: CHIA enables principled, scalable, and reproducible research on AI-driven hardware/software co-design, accelerating innovation across computer architecture, systems, compilers, and VLSI.