Hey AI, Generate Me a Hardware Code! Agentic AI-based Hardware Design & Verification

Modern Integrated Circuits (ICs) are becoming increasingly complex, and so is their development process. Hardware design verification entails a methodical and disciplined approach to the planning, development, execution, and sign-off of functionally correct hardware designs. This tedious process requires significant effort and time to ensure a bug-free tape-out. The field of Natural Language Processing has undergone a significant transformation with the advent of Large Language Models (LLMs). These powerful models, often referred to as Generative AI (GenAI), have revolutionized how machines understand and generate human language, enabling unprecedented advancements in a wide array of applications, including hardware design verification. This paper presents an agentic AI-based approach to hardware design verification, which empowers AI agents, in collaboration with Human-in-the-Loop (HITL) intervention, to engage in a more dynamic, iterative, and self-reflective process, ultimately performing end-to-end hardware design and verification. This methodology is evaluated on five open-source designs, achieving over $95 \%$ coverage with reduced verification time while demonstrating superior performance, adaptability, and configurability.

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Publication Details

Published
2025-08-25
DOI
https://doi.org/10.1109/sbcci66862.2025.11218681
Citations
3
Primary Topic
Embedded Systems Design Techniques
Type
article
Field-Weighted Citation Impact
6.81
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article

Hey AI, Generate Me a Hardware Code! Agentic AI-based Hardware Design & Verification

Djones Lettnin, Aman Kumar, Wolfgang Kunz, Sebastian Simon et al.
3 citations
Embedded Systems Design Techniques
6.81
article

Hey AI, Generate Me a Hardware Code! Agentic AI-based Hardware Design & Verification

Djones Lettnin, Aman Kumar, Wolfgang Kunz, Sebastian Simon, Deepak Narayan Gadde, Keerthan Kopparam Radhakrishna, Vaisakh Naduvodi Viswambharan
article en
3 citations

Abstract

Modern Integrated Circuits (ICs) are becoming increasingly complex, and so is their development process. Hardware design verification entails a methodical and disciplined approach to the planning, development, execution, and sign-off of functionally correct hardware designs. This tedious process requires significant effort and time to ensure a bug-free tape-out. The field of Natural Language Processing has undergone a significant transformation with the advent of Large Language Models (LLMs). These powerful models, often referred to as Generative AI (GenAI), have revolutionized how machines understand and generate human language, enabling unprecedented advancements in a wide array of applications, including hardware design verification. This paper presents an agentic AI-based approach to hardware design verification, which empowers AI agents, in collaboration with Human-in-the-Loop (HITL) intervention, to engage in a more dynamic, iterative, and self-reflective process, ultimately performing end-to-end hardware design and verification. This methodology is evaluated on five open-source designs, achieving over $95 \%$ coverage with reduced verification time while demonstrating superior performance, adaptability, and configurability.

Infineon Technologies (Germany) (DE), University of Koblenz and Landau (DE), Infineon Technologies (Singapore) (SG)
Openalex Percentile: Top 3%
Embedded Systems Design Techniques
6.81
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Hey AI, Generate Me a Hardware Code! Agentic AI-based Hardware Design & Verification — Djones Lettnin, Aman Kumar, et al. · (2025) | TGRS Research Map | TGRS