Abstract: AI is poised to revolutionize hardware design just as it has transformed software—but the path is more complex, more domain-specific, and rich with opportunity. In this keynote, we explore how large language models and agentic systems are reshaping the hardware design stack, with RTL coding as a proving ground.
We trace the evolution from post-training approaches that deliver high-quality Verilog through synthetic data generation and reasoning-augmented test time compute, to agentic systems capable of autonomous repair and synthesis using planning and waveform feedback.
We’ll highlight frontier works in agentic RTL optimization for PPA, debug assistance for formal verification, and broader design task orchestration with dynamic self-improving agents.
These examples hint at a larger future: AI agents that integrate with hardware design tools, reason over hardware-specific languages, and automate the design and verification process end-to-end. Realizing this vision will require advances in agent/model co-optimization, toolchain integration, and domain-specific language programming—but the path to autonomous hardware design has already begun.
Bio: Mark Ren is Director of Design Automation Research at NVIDIA, driving innovations in AI and GPU-accelerated tools that enhance chip design quality and productivity. He brings over 25 years of research experience in EDA at IBM and NVIDIA. His work has been widely published and adopted in industry, and has received best paper awards at leading conferences such as DAC, ISPD, ICLAD, and MLCAD, as well as in the TCAD journal. He holds a PhD from the University of Texas at Austin and is an IEEE Fellow.