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Fast Inference of Deep Neural Networks for Real-time Partic..:

, In: Proceedings of the 2019 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays,

Duarte, Javier ; Han, Song ; Harris, Philip... - p. 305 ff. , 2019

Link: https://dl.acm.org/doi/10.1145/3289602.3293986

RT 
T1 <cTitle>Proceedings of the 2019 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays</cTitle>: T1 <Title>Fast Inference of Deep Neural Networks for Real-time Particle Physics Applications</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3293986&Exemplar=1&LAN=DE
				
A1 Duarte, Javier
A1 Han, Song
A1 Harris, Philip
A1 Jindariani, Sergo
A1 Kreinar, Edward
A1 Kreis, Benjamin
A1 Loncar, Vladimir
A1 Ngadiuba, Jennifer
A1 Pierini, Maurizio
A1 Rankin, Dylan
A1 Rivera, Ryan
A1 Summers, Sioni
A1 Tran, Nhan
A1 Wu, Zhenbin
PB ACM
YR 2019
K1 fast-inference
K1 high level synthesis
K1 hls4ml
K1 machine learning
K1 multilayer perceptron
K1 neural network
K1 physics
K1 Computing methodologies
K1 Machine learning
K1 Machine learning approaches
K1 Neural networks
K1 Computer systems organization
K1 Architectures
K1 Other architectures
K1 Real-time systems
K1 Real-time system architecture
K1 Hardware
K1 Integrated circuits
K1 Reconfigurable logic and FPGAs
K1 Reconfigurable logic applications
K1 Hardware accelerators
K1 High-speed input / output
K1 Programmable interconnect
K1 Applied computing
K1 Physical sciences and engineering
K1 Physics
SP 305 ff.
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3289602.3293986
DO https://dl.acm.org/doi/10.1145/3289602.3293986
SF ELIB - SuUB Bremen

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