3 citations · 5 across the 5 of their papers we have counts for
5 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…
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…
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…
K-SpecPart: Supervised embedding algorithms and cut overlay for improved hypergraph partitioning
Ismail Bustany, Andrew B. Kahng, Ioannis Koutis +2
State-of-the-art hypergraph partitioners follow the multilevel paradigm that constructs multiple levels of progressively coarser hypergraphs that are used to drive cut refinement o…
PROBE3.0: A Systematic Framework for Design-Technology Pathfinding with Improved Design Enablement
Suhyeong Choi, Jinwook Jung, Andrew B. Kahng +4
We propose a systematic framework to conduct design-technology pathfinding for PPAC in advanced nodes. Our goal is to provide configurable, scalable generation of process design ki…