FPGA-Optimized Hardware Accelerator for Fast Fourier Transform and Singular Value Decomposition in AI

Fuente: arXiv
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Autori principali: Ding, Hong, Kang, Chia Chao, Xi, SuYang, Liu, Zehang, Zhang, Xuan, Ding, Yi
Natura: Preprint
Pubblicazione: 2025
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author Ding, Hong
Kang, Chia Chao
Xi, SuYang
Liu, Zehang
Zhang, Xuan
Ding, Yi
author_facet Ding, Hong
Kang, Chia Chao
Xi, SuYang
Liu, Zehang
Zhang, Xuan
Ding, Yi
contents This research introduces an FPGA-based hardware accelerator to optimize the Singular Value Decomposition (SVD) and Fast Fourier transform (FFT) operations in AI models. The proposed design aims to improve processing speed and reduce computational latency. Through experiments, we validate the performance benefits of the hardware accelerator and show how well it handles FFT and SVD operations. With its strong security and durability, the accelerator design achieves significant speedups over software implementations, thanks to its modules for data flow control, watermark embedding, FFT, and SVD.
format Preprint
id arxiv_https___arxiv_org_abs_2504_10411
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle FPGA-Optimized Hardware Accelerator for Fast Fourier Transform and Singular Value Decomposition in AI
Ding, Hong
Kang, Chia Chao
Xi, SuYang
Liu, Zehang
Zhang, Xuan
Ding, Yi
Hardware Architecture
This research introduces an FPGA-based hardware accelerator to optimize the Singular Value Decomposition (SVD) and Fast Fourier transform (FFT) operations in AI models. The proposed design aims to improve processing speed and reduce computational latency. Through experiments, we validate the performance benefits of the hardware accelerator and show how well it handles FFT and SVD operations. With its strong security and durability, the accelerator design achieves significant speedups over software implementations, thanks to its modules for data flow control, watermark embedding, FFT, and SVD.
title FPGA-Optimized Hardware Accelerator for Fast Fourier Transform and Singular Value Decomposition in AI
topic Hardware Architecture
url https://arxiv.org/abs/2504.10411