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

2024/05/25 by S. Arash Sheikholeslam, A. Ivanov, Sheikholeslam, Seyed Arash +1 · 2 citations
Computer Science · #Model-Driven Software Engineering Techniques

paper · pdf · doi:10.48550/arxiv.2405.16072

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: \urlhttps://github.com/sarashs/FPGA_AGI

Cited by

• Revolution or Hype? Seeking the Limits of Large Models in Hardware Design
• SAGE-HLS: Syntax-Aware AST-Guided LLM for High-Level Synthesis Code Generation

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