Výsledky vyhledávání - "Hoppe, Dennis"

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Containerisation for High Performance Computing Systems: Survey and Prospects

Autor: Zhou, Naweiluo, Zhou, Huan, Hoppe, Dennis

Containers improve the efficiency in application deployment and thus have been widely utilised on Cloud and lately in High Performance Computing (HPC) environments. Containers encapsulate complex programs with their dependencies in isolated environme

Externí odkaz: http://arxiv.org/abs/2212.08717

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Monitoring in the Clouds: Comparison of ECO2Clouds and EXCESS Monitoring Approaches

Autor: Skvortsov, Pavel, Hoppe, Dennis, Tenschert, Axel, Gienger, Michael

With the increasing adoption of private cloud infrastructures by providers and enterprises, the monitoring of these infrastructures is becoming crucial. The rationale behind monitoring is manifold: reasons include saving energy, lowering costs, and b

Externí odkaz: http://arxiv.org/abs/1601.07355

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Akademický článek

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Container orchestration on HPC systems through Kubernetes

Autor: Zhou, Naweiluo, Georgiou, Yiannis, Pospieszny, Marcin, Zhong, Li, Zhou, Huan, Niethammer, Christoph, Pejak, Branislav, Marko, Oskar, Hoppe, Dennis

Publikováno v: Journal of Cloud Computing: Advances, Systems and Applications, Vol 10, Iss 1, Pp 1-14 (2021)

Containerisation demonstrates its efficiency in application deployment in Cloud Computing. Containers can encapsulate complex programs with their dependencies in isolated environments making applications more portable, hence are being adopted in High

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::106f2db9fbc8505b51bff130bbea390a

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Parallel DBSCAN-Martingale estimation of the number of concepts for automatic satellite image clustering

Autor: Gialampoukidis, Ilias, Andreadis, Stelios, Pantelidis, Nick, Sameed Hayat, Zhong, Li, Bakratsas, Marios, Hoppe, Dennis, Vrochidis, Stefanos, Kompatsiaris, Ioannis

Publikováno v: Proceedings of the 28th International Conference on Multimedia Modeling (MMM 2022)

The necessity of organising big streams of Earth Observation (EO) data induces the efficient clustering of image patches, deriving from satellite imagery, into groups. Since the different concepts of the satellite image patches are not known a priori

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5327b613f0b815d0d2a01a8e7998f80b

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