An Empirical Comparision of LLM-based Hardware Design and High-level Synthesis

Field-Programmable Gate Arrays (FPGAs) are increasingly used for accelerating diverse applications due to their reconfigurability and ability to implement custom hardware architectures. However, programming FPGAs remains challenging, traditionally relying on low-level Hardware Description Languages (HDLs) like Verilog, which are intricate and time-consuming. High-Level Synthesis (HLS) tools, such as Vitis HLS, have emerged to address these issues by allowing hardware functionality description in high-level languages like C/C++, but they come with their own limitations, including less efficient hardware implementations, delay overhead caused by conservative scheduling strategies, and unpredictable solutions due to semantic differences between software and hardware.

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Publication Details

Published
2025-02-26
DOI
https://doi.org/10.1145/3706628.3708861
Primary Topic
VLSI and Analog Circuit Testing
Type
article
Field-Weighted Citation Impact
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article

An Empirical Comparision of LLM-based Hardware Design and High-level Synthesis

Kexing Zhou, Youwei Xiao, Yun Liang, Fan Cui
VLSI and Analog Circuit Testing
article

An Empirical Comparision of LLM-based Hardware Design and High-level Synthesis

Kexing Zhou, Youwei Xiao, Yun Liang, Fan Cui
article en

Abstract

Field-Programmable Gate Arrays (FPGAs) are increasingly used for accelerating diverse applications due to their reconfigurability and ability to implement custom hardware architectures. However, programming FPGAs remains challenging, traditionally relying on low-level Hardware Description Languages (HDLs) like Verilog, which are intricate and time-consuming. High-Level Synthesis (HLS) tools, such as Vitis HLS, have emerged to address these issues by allowing hardware functionality description in high-level languages like C/C++, but they come with their own limitations, including less efficient hardware implementations, delay overhead caused by conservative scheduling strategies, and unpredictable solutions due to semantic differences between software and hardware.

Peking University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 97%
VLSI and Analog Circuit Testing
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