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cs.AR2025
EvoVerilog: Large Langugage Model Assisted Evolution of Verilog Code
Ping Guo, Yiting Wang, Wanghao Ye +5
Large Language Models (LLMs) have demonstrated great potential in automating the generation of Verilog hardware description language code for hardware design. This automation is cr…
cs.AR2025
MCP4EDA: LLM-Powered Model Context Protocol RTL-to-GDSII Automation with Backend Aware Synthesis Optimization
Yiting Wang, Wanghao Ye, Yexiao He +3
This paper presents MCP4EDA, the first Model Context Protocol server that enables Large Language Models (LLMs) to control and optimize the complete open-source RTL-to-GDSII design…
cs.AR2025
SymRTLO: Enhancing RTL Code Optimization with LLMs and Neuron-Inspired Symbolic Reasoning
Yiting Wang, Wanghao Ye, Ping Guo +11
Optimizing Register Transfer Level (RTL) code is crucial for improving the power, performance, and area (PPA) of digital circuits in the early stages of synthesis. Manual rewriting…