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SynthAI: A Multi Agent Generative AI Framework for Automated Modular HLS Design Generation

Artificial Intelligence 2024-09-24 v4

Abstract

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}

Keywords

Cite

@article{arxiv.2405.16072,
  title  = {SynthAI: A Multi Agent Generative AI Framework for Automated Modular HLS Design Generation},
  author = {Seyed Arash Sheikholeslam and Andre Ivanov},
  journal= {arXiv preprint arXiv:2405.16072},
  year   = {2024}
}

Comments

This work is in progress and we will be updating it

R2 v1 2026-06-28T16:39:53.097Z