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Architecture to Distribute Deep Learning Models on Containers and Virtual Machines for Industry 4.0
30 décembre 2023, HE en HainautActe de conférence ou de colloqueeep learning (DL) is increasingly used in industry, especially in industry 4.0. Thanks to DL, it possible to better prevent breakdowns and manufacturing defects. DL models are becoming more and more complex and efficient, requiring significant compute resources and compute time. The use of Graphic Processing Units (GPUs) makes it possible to speed up processing but at a higher cost. An alternative ... -
Conception de l'identité graphique et de la signalétique du nouveau MICE TournaiXpo
2021, HE en HainautTFETFE Techniques Graphiques -
Création d’un site web et conception d’armes pour l’ASBL 7RAPL
2021, HE en HainautTFETFE Techniques Graphiques -
Distributed Deep Learning: From Single-Node to Multi-Node Architecture
2022, HE en HainautArticle scientifiqueDuring the last years, deep learning (DL) models have been used in several applications with large datasets and complex models. These applications require methods to train models faster, such as distributed deep learning (DDL). This paper proposes an empirical approach aiming to measure the speedup of DDL achieved by using different parallelism strategies on the nodes. Local parallelism is considered ... -
KIT' À TOUT PLANTER - Le kit potager à destination des citadins
2020, HE en HainautTFETFE Techniques Graphiques -
RÉALISATION D'UN JEU DE SOCIÉTÉ COOPÉRATIF AVEC TABLETOP SIMULATOR
2020, HE en HainautTFETFE Techniques Graphiques