A2H-MAS: An Algorithm-to-HLS Multi-Agent System for Automated and Reliable FPGA Implementation
Jie Lei, Ruofan Jia, J. Andrew Zhang, Hao Zhang

TL;DR
A2H-MAS is a multi-agent system that automates the translation of algorithms from MATLAB to FPGA hardware using HLS, ensuring correctness, efficiency, and robustness in wireless communication applications.
Contribution
It introduces a modular, hierarchical multi-agent framework that automates algorithm-to-HLS translation with validation, co-design, and domain-specific optimization.
Findings
Produces functionally correct FPGA designs
Achieves resource efficiency and low latency
Demonstrates robustness on wireless algorithms
Abstract
Bridging the gap between algorithm development and hardware realization remains a persistent challenge, particularly in latency- and resource-constrained domains such as wireless communication. While MATLAB provides a mature environment for algorithm prototyping, translating these models into efficient FPGA implementations via High-Level Synthesis (HLS) often requires expert tuning and lengthy iterations. Recent advances in large language models (LLMs) offer new opportunities for automating this process. However, existing approaches suffer from hallucinations, forgetting, limited domain expertise, and often overlook key performance metrics. To address these limitations, we present A2H-MAS, a modular and hierarchical multi-agent system. At the system level, A2H-MAS assigns clearly defined responsibilities to specialized agents and uses standardized interfaces and execution-based…
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