gem5 Co-Pilot: AI Assistant Agent for Architectural Design Space Exploration
Zuoming Fu, Alex Manley, Mohammad Alian

TL;DR
This paper introduces gem5 Co-Pilot, an AI assistant leveraging Large Language Models to automate and accelerate computer architecture design space exploration, optimizing parameters efficiently with minimal user input.
Contribution
We developed gem5 Co-Pilot, a novel AI agent with a GUI, a dedicated language, and a database system to enhance design space exploration in computer architecture.
Findings
Successfully identified optimal parameters for design constraints
Reduced time and user effort in exploration process
Compared favorably with baseline models in experiments
Abstract
Generative AI is increasing the productivity of software and hardware development across many application domains. In this work, we utilize the power of Large Language Models (LLMs) to develop a co-pilot agent for assisting gem5 users with automating design space exploration. Computer architecture design space exploration is complex and time-consuming, given that numerous parameter settings and simulation statistics must be analyzed before improving the current design. The emergence of LLMs has significantly accelerated the analysis of long-text data as well as smart decision making, two key functions in a successful design space exploration task. In this project, we first build gem5 Co-Pilot, an AI agent assistant for gem5, which comes with a webpage-GUI for smooth user interaction, agent automation, and result summarization. We also implemented a language for design space exploration,…
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Taxonomy
TopicsMachine Learning in Materials Science · Artificial Intelligence in Games · Model-Driven Software Engineering Techniques
