Presentation
Agentic AI Partition And Floorplan Assistance For PCIe/CXL Subsystem Physical Design
DescriptionThe deployment of advanced high-speed protocols (e.g., PCIe Gen6/CXL) in multi-billion-gate designs creates a severe "Logical-Physical Gap," where traditional implementation flows suffer from unmanageable runtimes and convergence volatility. This work introduces a novel Cognitive Agentic Framework that orchestrates multi-objective partitioning and semantic-driven floorplanning to bridge this divide. Unlike conventional methodologies relying on blind min-cut algorithms or static placement rules, our approach utilizes HGNN to predict physical feasibility during logical partitioning, optimizing for size balance, boundary timing, and data stream integrity. Furthermore, we propose Dataflow-Driven Vision-Language Reinforced Semantic Floorplanning, where a Large Multimodal Model functions as a "visual perception sensor" within a physics-based force field. This allows the agent to iteratively "see" congestion hotspots and dynamically adjust repulsion forces to enforce semantic consistency. By embedding physical awareness into the architectural phase, our framework reduces the design iteration cycle, achieving superior PPA metrics and deterministic timing closure compared to standard industrial flows.
Event Type
Engineering Poster
TimeTuesday, July 285:00pm - 6:00pm PDT
LocationDAC Pavilion, Exhibit Floor