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CNN-DMA : A Predictable and Scalable Direct Memory Acces..:

, In: Proceedings of the 2021 on Great Lakes Symposium on VLSI,

Wang, Zheng ; Wang, Zhuo ; Liao, Jian... - p. 115-121 , 2021

Link: https://dl.acm.org/doi/10.1145/3453688.3461496

RT 
T1 <cTitle>Proceedings of the 2021 on Great Lakes Symposium on VLSI</cTitle>: T1 <Title>CNN-DMA				: A Predictable and Scalable Direct Memory Access Engine for Convolutional Neural Network with Sliding-window Filtering</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3461496&Exemplar=1&LAN=DE
				
A1 Wang, Zheng
A1 Wang, Zhuo
A1 Liao, Jian
A1 Chen, Chao
A1 Yang, Yongkui
A1 Dong, Bo
A1 Chen, Weiguang
A1 Chen, Wenxuan
A1 Lei, Ming
A1 Guo, Weiyu
A1 Chen, Rui
A1 Peng, Yi
A1 Yu, Zhibin
PB ACM
YR 2021
K1 direct memory access
K1 machine learning accelerator
K1 sliding-window filtering
K1 Hardware
K1 Very large scale integration design
K1 Application-specific VLSI designs
K1 Application specific integrated circuits
K1 Computer systems organization
K1 Architectures
K1 Other architectures
K1 Neural networks
K1 Data flow architectures
K1 Integrated circuits
K1 Semiconductor memory
K1 Dynamic memory
SP 115
OP 121
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3453688.3461496
DO https://dl.acm.org/doi/10.1145/3453688.3461496
SF ELIB - SuUB Bremen

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