TY  - CONF
AU  - Cavallaro, Gabriele
AU  - Kozlov, Valentin
AU  - Götz, Markus
AU  - Riedel, Morris
TI  - Remote Sensing Data Analytics with the Udocker Container Tool using Multi-GPU Deep Learning Systems
M1  - FZJ-2019-01785
PY  - 2019
AB  - Multi-GPU systems are in continuous development todeal with the challenges of intensive computational big dataproblems. On the one hand, parallel architectures provide atremendous computation capacity and outstanding scalability.On the other hand, the production path in multi-user environmentsfaces several roadblocks since they do not grant rootprivileges to the users. Containers provide flexible strategiesfor packing, deploying and running isolated applicationprocesses within multi-user systems and enable scientific reproducibility.This paper describes the usage and advantagesthat the uDocker container tool offers for the developmentof deep learning models in the described context. The experimentalresults show that uDocker is more transparent todeploy for less tech-savvy researchers and allows the applicationto achieve processing time with negligible overheadcompared to an uncontainerized environment.
T2  - Conference on Big Data from Space (BiDS'19)
CY  - 19 Feb 2019 - 21 Feb 2019, Munich (Germany)
Y2  - 19 Feb 2019 - 21 Feb 2019
M2  - Munich, Germany
LB  - PUB:(DE-HGF)24
UR  - https://juser.fz-juelich.de/record/861288
ER  -