1 citations · 1 across the 13 of their papers we have counts for
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Agentic Hardware Design as Repository-Level Code Evolution
Cunxi Yu, Chenhui Deng, Nathaniel Pinckney +1
We present HORIZON, a self-evolving agent framework that treats hardware design as repository-level code evolution. A Markdown harness is compiled into a project pack containing do…
AUTOGATE: Automated Clock Gating via Toggling-Aware LLM-based RTL Rewriting
Yiting Wang, Chenhui Deng, Chia-Tung Ho +6
Fine-grain clock gating (FGCG) is among the most effective techniques for reducing dynamic power, yet current FGCG optimization flows remain largely manual. Recent LLM-based RTL op…
ACE-RTL: When Agentic Context Evolution Meets RTL-Specialized LLMs
Chenhui Deng, Zhongzhi Yu, Guan-Ting Liu +3
Recent advances in LLMs have sparked growing interest in applying them to hardware design automation, particularly for accurate RTL code generation. Prior efforts follow two largel…
GRPO with State Mutations: Improving LLM-Based Hardware Test Plan Generation
Dimple Vijay Kochar, Nathaniel Pinckney, Guan-Ting Liu +4
RTL design often relies heavily on ad-hoc testbench creation early in the design cycle. While large language models (LLMs) show promise for RTL code generation, their ability to re…
ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation
Chenhui Deng, Yun-Da Tsai, Guan-Ting Liu +2
Recent advances in large language models (LLMs) have enabled near-human performance on software coding benchmarks, but their effectiveness in RTL code generation remains limited du…
Marco: Configurable Graph-Based Task Solving and Multi-AI Agents Framework for Hardware Design
Chia-Tung Ho, Jing Gong, Yunsheng Bai +3
Hardware design presents numerous challenges stemming from its complexity and advancing technologies. These challenges result in longer turn-around-time (TAT) for optimizing perfor…
ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation
Chenhui Deng, Yunsheng Bai, Haoxing Ren
Recent advancements in large language models (LLMs) have expanded their application across various domains, including chip design, where domain-adapted chip models like ChipNeMo ha…