Summary of Synthai: a Multi Agent Generative Ai Framework For Automated Modular Hls Design Generation, by Seyed Arash Sheikholeslam et al.
SynthAI: A Multi Agent Generative AI Framework for Automated Modular HLS Design Generation
by Seyed Arash Sheikholeslam, Andre Ivanov
First submitted to arxiv on: 25 May 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel approach to automated High-Level Synthesis (HLS) design creation is presented in this paper, dubbed SynthAI. This method integrates ReAct agents, Chain-of-Thought prompting, web search technologies, and the Retrieval-Augmented Generation framework within a structured decision graph. By decomposing complex hardware design tasks into manageable modules, SynthAI enables the generation of synthesizable designs that closely adhere to user-specified objectives and requirements. The paper demonstrates the capabilities of SynthAI through case studies, showcasing its ability to create complex, multi-module logic designs from a single prompt. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary SynthAI is a new way to make computer chips using artificial intelligence (AI). It breaks down big design problems into smaller pieces that are easier to solve. This helps AI create chip designs that match what people want them to do. The paper shows how SynthAI works by giving examples of complex designs it can make from simple prompts. |
Keywords
» Artificial intelligence » Prompt » Prompting » Retrieval augmented generation
