2 citations · 2 across the 4 of their papers we have counts for
4 papers
Physics-Guided Geometric Diffusion for Macro Placement Generation
Jongho Yoon, Jinsung Jeon, Seokhyeong Kang
Macro placement is a pivotal stage in VLSI physical design, fundamentally determining the overall chip performance. Recent data-driven placement methods have demonstrated significa…
REvolution: An Evolutionary Framework for RTL Generation driven by Large Language Models
Kyungjun Min, Kyumin Cho, Junhwan Jang +1
Large Language Models (LLMs) are used for Register-Transfer Level (RTL) code generation, but they face two main challenges: functional correctness and Power, Performance, and Area…
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…
Hybrid Circuit Mapping: Leveraging the Full Spectrum of Computational Capabilities of Neutral Atom Quantum Computers
Ludwig Schmid, Sunghye Park, Seokhyeong Kang +1
Quantum computing based on Neutral Atoms (NAs) provides a wide range of computational capabilities, encompassing high-fidelity long-range interactions with native multi-qubit gates…