PUMA publications for /tag/computing%20dataMon Apr 28 00:38:40 CEST 2025Surveillance Graphs: Vulgarity and Cloud Orthodoxy in Linked Data Infrastructures2023ai artificial cloud computing data infrastructure intelligence linked semantic surveillance web Tue Jun 26 09:18:47 CEST 2018IEEE Internet Computingmay364-69The Social Compute Unit152011Collaboration computing data network soc2018 social workflow Wed Feb 21 16:57:28 CET 20182017 24th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)nov1-6A cloud-based control architecture design for the interaction of industrial robots with soft objects2017architecture cloud cloud-based computing control data grk2198 path Mon Feb 05 16:32:51 CET 20182017 24th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)nov1-6A cloud-based control architecture design for the interaction of industrial robots with soft objects2017architecture cloud cloud-based computing control data path Fri Jan 29 09:34:55 CET 2016Utility and Cloud Computing (UCC)December579 - 584A Cloud-based Data Farming Platform for Molecular Dynamics Simulations2014Cloud Data HLRS MD SCOPE computing farming myown simulations With the cloud paradigm and the concept of everything as a service (XasS), our ability to leverage the potential of distributed computing resources seems greater than ever. On the other hand, data farming is a methodology based on the idea that by repeatedly running a simulation model on a vast parameter space, enough output data can be gathered to provide an meaningful insight into relations between the model's properties and its behaviours, with respect to the simulation's input parameters. In this paper, we present an extension of a data farming computing platform, named Scalarm, and it's evaluation in the context of molecular dynamics (MD) simulations on heterogeneous resources, such as clusters and cloud systems. As a case study, this paper demonstrates how MD simulations can be run with Scalarm on different infrastructures easily without requiring any modifications to the source code of the original MD simulation program. Finally, results from nano droplet simulation runs are presented, that show the advantages of the Scalarm platform for running MD simulations on a heterogeneous infrastructure -- not only for collecting pure numeric data, but also for automated post processing and visualization of the results.Fri Oct 30 15:37:24 CET 2015The Need to Comprehend Clouds: Why We Still Can't Use Clouds Properly2012cloud computing data hlrs myown Fri Oct 30 15:33:17 CET 2015Adaptable and Distributed Program Execution2011cloud computing data distributed hlrs myown Fri Oct 30 15:32:05 CET 2015Beyond Clouds: Towards Real Utility Computing2011HLRS cloud computing data myown computing dataCommunity for tag(s) computing data