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The ever-growing popularity of large language models (LLMs) has resulted in their increasing adoption for hardware design and verification. Prior research has attempted to assess the capability of LLMs to automate digital hardware design by…

Hardware Architecture · Computer Science 2024-08-07 Sneha Swaroopa , Rijoy Mukherjee , Anushka Debnath , Rajat Subhra Chakraborty

Large Language Models (LLMs) have recently achieved strong performance in software code generation. However, applying them to hardware description languages (HDLs), such as Verilog, remains challenging because high-quality training data are…

Hardware Architecture · Computer Science 2026-04-21 Yan Tan , Tong Liu , Xiangchen Meng , Yangdi Lyu

Large language models (LLMs) have demonstrated impressive capabilities in generating software code for high-level programming languages such as Python and C++. However, their application to hardware description languages, such as Verilog,…

Programming Languages · Computer Science 2026-03-13 Yan Tan , Xiangchen Meng , Zijun Jiang , Yangdi Lyu

Automating hardware design could obviate a significant amount of human error from the engineering process and lead to fewer errors. Verilog is a popular hardware description language to model and design digital systems, thus generating…

Programming Languages · Computer Science 2022-12-22 Shailja Thakur , Baleegh Ahmad , Zhenxing Fan , Hammond Pearce , Benjamin Tan , Ramesh Karri , Brendan Dolan-Gavitt , Siddharth Garg

Large language models (LLMs) have demonstrated strong capabilities in generating Verilog code from natural language descriptions. However, Verilog code inherently encodes structural information of hardware circuits. Effectively leveraging…

Hardware Architecture · Computer Science 2025-10-21 Jiayu Zhao , Song Chen

Large language models (LLMs) have demonstrated impressive capabilities in generating software code for high-level programming languages such as Python and C++. However, their application to hardware description languages, such as Verilog,…

Hardware Architecture · Computer Science 2025-09-11 Yan Tan , Xiangchen Meng , Zijun Jiang , Yangdi Lyu

High-level synthesis (HLS) transforms an algorithmic description of hardware from a higher abstraction (e.g., C/C++) into a register-transfer level (RTL) design, offering reduced development time and greater flexibility in design space…

Hardware Architecture · Computer Science 2026-04-27 Xiaofeng Zhou , Linfeng Du , Guangyu Hu , Sharad Sinha , Hongce Zhang , Wei Zhang

Large language models (LLMs) have shown strong performance in Verilog generation from natural language description. However, ensuring the functional correctness of the generated code remains a significant challenge. This paper introduces a…

Hardware Architecture · Computer Science 2025-04-23 Ning Wang , Bingkun Yao , Jie Zhou , Yuchen Hu , Xi Wang , Nan Guan , Zhe Jiang

Large Language Models (LLMs) have demonstrated promising capabilities in generating Verilog code from module specifications. To improve the quality of such generated Verilog codes, previous methods require either time-consuming manual…

Hardware Architecture · Computer Science 2025-02-04 Zhuorui Zhao , Ruidi Qiu , Ing-Chao Lin , Grace Li Zhang , Bing Li , Ulf Schlichtmann

The increasing complexity and demand for faster, energy-efficient hardware designs necessitate innovative High-Level Synthesis (HLS) methodologies. This paper explores the potential of Large Language Models (LLMs) to streamline or replace…

Hardware Architecture · Computer Science 2024-08-21 Yuchao Liao , Tosiron Adegbija , Roman Lysecky

Recently, there has been a surging interest in using large language models (LLMs) for Verilog code generation. However, the existing approaches are limited in terms of the quality of the generated Verilog code. To address such limitations,…

Machine Learning · Computer Science 2024-10-08 Bardia Nadimi , Hao Zheng

The increasing popularity of large language models (LLMs) has paved the way for their application in diverse domains. This paper proposes a benchmarking framework tailored specifically for evaluating LLM performance in the context of…

Machine Learning · Computer Science 2023-12-12 Mingjie Liu , Nathaniel Pinckney , Brucek Khailany , Haoxing Ren

In today's rapidly evolving field of electronic design automation (EDA), the complexity of hardware designs is increasing, necessitating more sophisticated automation solutions. High-level synthesis (HLS), as a pivotal solution, automates…

Programming Languages · Computer Science 2025-08-06 M Zafir Sadik Khan , Nowfel Mashnoor , Mohammad Akyash , Kimia Azar , Hadi Kamali

We present \synver{}, a novel synthesis and verification framework for C programs, that deploys a Large Language Model (LLM) to search for a candidate program that satisfies the given specification. Our key idea is to impose syntactic and…

Programming Languages · Computer Science 2025-10-21 Prasita Mukherjee , Benjamin Delaware

Large Language Models (LLMs) show promise in automated software engineering, yet their guarantee of correctness is frequently undermined by erroneous or hallucinated code. To enforce model honesty, formal verification requires LLMs to…

Software Engineering · Computer Science 2026-04-27 Md Erfan , Md Kamal Hossain Chowdhury , Ahmed Ryan , Md Rayhanur Rahman

Large language models (LLMs) have recently emerged as a promising approach for automating Verilog code generation; however, existing methods primarily emphasize syntactic correctness and often rely on commercial models or external…

Large language models (LLMs) have demonstrated significant potential in automating hardware synthesis, yet substantial barriers remain for industrial-scale, datapath-centric designs due to ambiguous specifications and a lack of formal…

Hardware Architecture · Computer Science 2026-03-11 Kezhi Li , Min Li , Xiangyu Wen , Shibo Zhao , Jieying Wu , Junhua Huang , Qiang Xu

Test generation has been a critical and labor-intensive process in hardware design verification. Recently, the emergence of Large Language Model (LLM) with their advanced understanding and inference capabilities, has introduced a novel…

Software Engineering · Computer Science 2025-01-03 Ruiyang Ma , Yuxin Yang , Ziqian Liu , Jiaxi Zhang , Min Li , Junhua Huang , Guojie Luo

Recent advances have demonstrated the promising capabilities of large language models (LLMs) in generating register-transfer level (RTL) code, such as Verilog. However, existing LLM-based frameworks still face significant challenges in…

Software Engineering · Computer Science 2025-09-09 Jian Zuo , Junzhe Liu , Xianyong Wang , Yicheng Liu , Navya Goli , Tong Xu , Hao Zhang , Umamaheswara Rao Tida , Zhenge Jia , Mengying Zhao

In the past few years, Large Language Models (LLMs) have exploded in usefulness and popularity for code generation tasks. However, LLMs still struggle with accuracy and are unsuitable for high-risk applications without additional oversight…

Software Engineering · Computer Science 2024-10-29 William Murphy , Nikolaus Holzer , Feitong Qiao , Leyi Cui , Raven Rothkopf , Nathan Koenig , Mark Santolucito
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