DSA-CNN: an fpga-integrated deformable systolic array for convolutional neural network acceleration

Yi Wan; Junfan Chen; Xiong Yang; Hailong Zhang; Chao Huang; Xianzhong Xie

doi:10.1007/s10489-024-05898-w

ScienceGate Book Chapters

JOURNAL ARTICLE

DSA-CNN: an fpga-integrated deformable systolic array for convolutional neural network acceleration

Yi Wan Junfan Chen Xiong Yang Hailong Zhang Chao Huang Xianzhong Xie

Year: 2024 Journal: Applied Intelligence Vol: 55 (1) Publisher: Springer Science+Business Media

DOI: 10.1007/s10489-024-05898-w

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Loop unrolling Field-programmable gate array Convolutional neural network Dataflow Application-specific integrated circuit Systolic array Gate array Scalability Parallel computing Embedded system Artificial intelligence Very-large-scale integration

Metrics

Cited By

1.59

FWCI (Field Weighted Citation Impact)

Refs

0.77

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Advanced Neural Network Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Memory and Neural Computing

Physical Sciences → Engineering → Electrical and Electronic Engineering

CCD and CMOS Imaging Sensors

Physical Sciences → Engineering → Electrical and Electronic Engineering

DSA-CNN: an fpga-integrated deformable systolic array for convolutional neural network acceleration

Metrics

Citation History

Topics

Related Documents

Systolic Array Based Convolutional Neural Network Inference on FPGA

Systolic Array for Neural Network Acceleration

Hardware aware Convolutional Neural Network (CNN) training acceleration

WinoCNN: Kernel Sharing Winograd Systolic Array for Efficient Convolutional Neural Network Acceleration on FPGAs

Research on FPGA Based Convolutional Neural Network Acceleration Method