CRADLE: Conversational RTL Design Space Exploration with LLM-based Multi-Agent Systems
By Lukas Krupp, Maximilian Schoffel, Elias Biehl, and Norbert Wehn ¨
RPTU University of Kaiserslautern-Landau, Kaiserslautern, Germany
Abstract
This paper presents CRADLE, a conversational framework for design space exploration of RTL designs using LLM-based multi-agent systems. Unlike existing rigid approaches, CRADLE enables user-guided flows with internal selfverification, correction, and optimization. We demonstrate the framework with a generator-critic agent system targeting FPGA resource minimization using state-of-the-art LLMs. Experimental results on the RTLLM benchmark show that CRADLE achieves significant reductions in resource usage with averages of 48% and 40% in LUTs and FFs across all benchmark designs.
Index Terms—LLM, Agents, Design Space Exploration, RTL
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