FluxEDA: A Unified Execution Infrastructure for Stateful Agentic EDA

2026-03-26

AI Summary

This work proposes a unified, stateful agent-based execution infrastructure for integrating large language models with electronic design automation (EDA) tools. Addressing the limitations of existing stateless scripting or request-response paradigms—which hinder iterative optimization in production environments—the architecture introduces a managed gateway interface coupled with persistent EDA tool instances. This enables, for the first time, an execution layer that supports state reuse, rollback, and collaborative iteration. By employing a structured request/response mechanism, the system facilitates state-preserving interactions with heterogeneous EDA tools. The approach is validated through two commercial use cases: post-routing timing engineering change orders (ECOs) and standard cell sublibrary optimization, where it successfully orchestrates multi-step analysis and refinement workflows, demonstrating its effectiveness and practicality in agent-driven EDA automation.

Technology Category

• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Multiagent Systems: Mechanism Design
• Machine Learning: Hardware-aware ML

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Economics, Online Markets and Human Computation: Architectures and workflows that use LLMs for crowd work
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Large language models and autonomous agents are increasingly explored for EDA automation, but many existing integrations still rely on script-level or request-level interactions, which makes it difficult to preserve tool state and support iterative optimization in real production-oriented environments. In this work, we present FluxEDA, a unified and stateful infrastructure substrate for agentic EDA. FluxEDA introduces a managed gateway-based execution interface with structured request and response handling. It also maintains persistent backend instances. Together, these features allow upper-layer agents and programmable clients to interact with heterogeneous EDA tools through preserved runtime state, rather than through isolated shell invocations. We evaluate the framework using two representative commercial backend case studies: automated post-route timing ECO and standard-cell sub-library optimization. The results show that FluxEDA can support multi-step analysis and optimization over real tool contexts, including state reuse, rollback, and coordinated iterative execution. These findings suggest that a stateful and governed infrastructure layer is a practical foundation for agent-assisted EDA automation.

Problem

• stateful execution
• agentic EDA
• tool state preservation
• iterative optimization
• EDA automation

Innovation

• stateful infrastructure
• agentic EDA
• managed gateway
• persistent backend
• iterative optimization