FluxEDA: A Unified Execution Infrastructure for Stateful Agentic EDA

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.

Figures (5)

• Figure 1: Comparison between traditional EDA workflows and the proposed unified FluxEDA, highlighting the shift from fragmented scripting and tool-specific orchestration to a cohesive, standardized framework for EDA tool integration.
• Figure 2: Overall software architecture of FluxEDA. The system organizes heterogeneous EDA environments into a five-layer stack that provides unified access, controlled capability exposure, and persistent tool execution for agentic and programmable workflows.
• Figure 3: Execution signal flow in FluxEDA. Agent requests are issued through task logic, forwarded by the RPC client and session manager to the Tcl gateway, resolved through registered api_* methods, and executed on managed EDA runtimes. Capability discovery, method metadata, typed results, artifacts, and execution status traverse the same structured path.
• Figure 4: Lifecycle of a managed backend instance in FluxEDA. After a tool process is created and bound to an instance_id, multiple requests can be routed to the same live instance before it is eventually reclaimed by runtime management.
• Figure 5: Search trajectory for Pareto-driven standard-cell sub-library selection. Blue arrows denote the area-driven exploration stage (A-Runs) from the minimal library toward low-area operating points. Red arrows denote the subsequent timing-recovery stage (T-Runs), where the agent first performs local probing around T-Run04 and then transitions to structure-guided restoration, eventually reaching T-Run11. Gray dashed arrows indicate alternative local probes.