9 papers
MAGE: Human-Like Macro Placement via Agentic Multimodal Reasoning
Andrew B. Kahng, Sayak Kundu, Bodhisatta Pramanik
Macro placement still requires substantial manual refinement in industrial physical design flows. We present MAGE (Macro Placement Agentic Engine), a multimodal multi-agent framewo…
ORFS-agent: Tool-Using Agents for Chip Design Optimization
Amur Ghose, Andrew B. Kahng, Sayak Kundu +1
Machine learning has been widely used to optimize complex engineering workflows across numerous domains. In integrated circuit design, modern flows (e.g., register-transfer level t…
Escaping Flatland: A Placement Flow for Enabling 3D FPGAs
Cong Hao, Andrew B. Kahng, Bodhisatta Pramanik +1
3D field-programmable gate arrays (FPGAs) promise higher performance through vertical integration. However, existing placement tools, largely inherited from 2D frameworks, fail to…
An Extended Study of Gear-Ratio-Aware Standard Cell Layout Generation for DTCO Exploration
Chung-Kuan Cheng, Andrew B. Kahng, Bill Lin +2
Advanced nodes decouple contacted poly pitch (CPP) and lower-metal pitch to improve routability. We present CPCell, an efficient standard-cell layout generation framework, to suppo…
ChipletPart: Cost-Aware Partitioning for 2.5D Systems
Alexander Graening, Puneet Gupta, Andrew B. Kahng +2
Industry adoption of chiplets has been growing as chiplets are a cost-effective option for making large, high-performance systems. Consequently, partitioning large systems into chi…
ArtNet: Hierarchical Clustering-Based Artificial Netlist Generator for ML and DTCO Application
Andrew B. Kahng. Seokhyeong Kang, Seonghyeon Park, Dooseok Yoon
In advanced nodes, optimization of power, performance and area (PPA) has become highly complex and challenging. Machine learning (ML) and design-technology co-optimization (DTCO) p…