8 papers
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…
Nemotron 3 Ultra: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
NVIDIA, :, Aaron Blakeman +571
We introduce Nemotron 3 Ultra, a 550 billion total and 55 billion active parameter Mixture-of-Experts Hybrid Mamba-Attention language model. We pre-trained Nemotron 3 Ultra on 20 t…
Trace2Skill: Verifier-Guided Skill Evolution for Long-Context EDA Agents
Zijian Du, Nathaniel Pinckney
Complex Verilog Design Problems (CVDP) challenge hardware LLM agents because solving them requires localizing verifier-relevant RTL, testbenches, include paths, and build dependenc…
Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
NVIDIA, :, Aakshita Chandiramani +544
We describe the pre-training, post-training, and quantization of Nemotron 3 Super, a 120 billion (active 12 billion) parameter hybrid Mamba-Attention Mixture-of-Experts model. Nemo…
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…