Description: Remote Sensing Data Analytics with the Udocker Container Tool using Multi-GPU Deep Learning Systems

This title appears in the Scientific Report : 2019

Remote Sensing Data Analytics with the Udocker Container Tool using Multi-GPU Deep Learning Systems

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...

Personal Name(s):	Cavallaro, Gabriele
	Kozlov, Valentin / Götz, Markus / Riedel, Morris
Contributing Institute:	Jülich Supercomputing Center; JSC
Imprint:	2019
Conference:	Conference on Big Data from Space (BiDS'19), Munich (Germany), 2019-02-19 - 2019-02-21
Document Type:	Poster
Research Program:	Designing and Enabling E-infrastructures for intensive Processing in a Hybrid DataCloud DEEP - Extreme Scale Technologies Data-Intensive Science and Federated Computing
Link:	OpenAccess OpenAccess
	Publikationsportal JuSER

Please use the identifier: http://hdl.handle.net/2128/21807 in citations.

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.