ArchBot: A Labour-free Processor Architecture Design Framework via Experienced LLM

Processors are the cornerstone of computing systems, yet their design process remains highly complex and labor-intensive. Current automated architecture design methods often rely on pre-configured models, limiting flexibility and requiring extensive manual effort. Additionally, challenges such as capturing architectural knowledge, optimizing parameters within constrained simulation times, and managing complex decision-making processes further complicate the task. To address these issues, we propose ArchBot, a labor-free processor architecture design framework leveraging large language models and reinforcement learning. ArchBot integrates a curated RISC-V architecture knowledge base, RL for microarchitecture exploration, and a machine-learning-based fast simulation model to accelerate optimization. It also uses LLMs to automate design requirement analysis and task decomposition, generating gem5 code as output. Experiments demonstrate that ArchBot achieves a 95% success rate in meeting design requirements, surpassing existing frameworks and offering a novel solution for automated processor design.