SynthAI: A Multi Agent Generative AI Framework for Automated Modular HLS Design Generation
<|reference_start|>SynthAI: A Multi Agent Generative AI Framework for Automated Modular HLS Design Generation: In this paper, we introduce SynthAI, a new method for the automated creation of High-Level Synthesis (HLS) designs. SynthAI integrates ReAct agents, Chain-of-Thought (CoT) prompting, web search technologies, and the Retrieval-Augmented Generation (RAG) framework within a structured decision graph. This innovative approach enables the systematic decomposition of complex hardware design tasks into multiple stages and smaller, manageable modules. As a result, SynthAI produces synthesizable designs that closely adhere to user-specified design objectives and functional requirements. We further validate the capabilities of SynthAI through several case studies, highlighting its proficiency in generating complex, multi-module logic designs from a single initial prompt. The SynthAI code is provided via the following repo: \url{https://github.com/sarashs/FPGA_AGI}<|reference_end|>
@article{sheikholeslam2024synthai:,
    title={SynthAI: A Multi Agent Generative AI Framework for Automated Modular HLS
  Design Generation},
    author={Seyed Arash Sheikholeslam, Andre Ivanov},
    journal={arXiv preprint arXiv:2405.16072},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.16072},
    primaryClass={cs.AI}
}