标题： SPICE助手：使用SPICE仿真工具的LLM用于开关模式电源的原理图设计 显示英文标题

标题： SPICEAssistant: LLM using SPICE Simulation Tools for Schematic Design of Switched-Mode Power Supplies

摘要： 目前最先进的大型语言模型（LLMs）在科学的许多领域中的各种任务中表现出色。 在电子设计自动化（EDA）领域，尚不清楚它们在多大程度上能够理解、适应和设计电子电路。 本文专注于将LLMs应用于印刷电路板（PCBs）上的开关模式电源（SMPS）设计。 在此背景下，LLMs面临的特殊挑战包括它们有限的能力来解释关键仿真工具如SPICE的结果以及多步骤的设计过程。 为了解决这些挑战，我们提出了SPICEAssistant，这是一个为LLM提供广泛工具选择的框架。 这些工具作为与SPICE的接口，使LLM能够灵活地与模拟器交互，以估计其对电路修改的影响。 为了评估SPICEAssistant的性能，我们定义了一个由256个问题组成的基准，用于测试将电路网表适应以满足不同SMPS设计任务的能力。 基准测试结果表明，仿真反馈有效提高了LLMs的SMPS设计能力。 越来越多的仿真迭代次数导致性能提升。 SPICEAssistant框架在基准测试中显著优于独立的LLM GPT-4o，提升了约38%。 显示英文摘要

摘要： State-of-the-art large language models (LLMs) show high performance across a wide range of tasks in many domains of science. In the field of electronic design automation (EDA), it is yet to be determined to what extent they are capable to understand, adapt, and dimension electronic circuits. This paper focuses on the application of LLMs to switched-mode power supply (SMPS) design on printed circuit boards (PCBs). Particular challenges for LLMs in this context include their limited ability to interpret results from key simulation tools like SPICE and the multi-step design process. To address these challenges, we suggest SPICEAssistant, a framework that provides a broad selection of tools to an LLM. The tools serve as an interface to SPICE, allowing the LLM to interact flexibly with the simulator to estimate the impact of its modifications to the circuit. To evaluate the performance of SPICEAssistant, we defined a benchmark consisting of 256 questions testing the ability to adapt circuit netlists to fulfil different SMPS design tasks. The benchmarking results show that simulation feedback effectively improves SMPS design capabilities of LLMs. An increasing number of simulation iterations leads to enhanced performance. The SPICEAssistant framework significantly outperforms the standalone LLM GPT-4o on the benchmark by approximately 38%.