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Article
Physically constrained generative adversarial networks for improving precipitation fields from Earth system models
Precipitation results from complex processes across many scales, making its accurate simulation in Earth system models (ESMs) challenging. Existing post-processing methods can improve ESM simulations locally b...
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Article
Open AccessClimate-induced hysteresis of the tropical forest in a fire-enabled Earth system model
Tropical rainforests are recognized as one of the terrestrial tip** elements which could have profound impacts on the global climate, once their vegetation has transitioned into savanna or grassland states. ...
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Article
Open AccessAlberta wildfire 2016: Apt contribution from anomalous planetary wave dynamics
In May-June 2016 the Canadian Province of Alberta suffered one of the most devastating wildfires in its history. Here we show that in mid-April to early May 2016 the large-scale circulation in the mid- and hig...
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Chapter and Conference Paper
FANTOMAS Fault Tolerance for Mobile Agents in Clusters
To achieve an efficient utilization of cluster systems, a proper programming and operating environment is required. In this context, mobile agents are of growing interest as base for distributed and parallel a...
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Chapter and Conference Paper
Migration and rollback transparency for arbitrary distributed applications in workstation clusters
Programmers and users of compute intensive scientific applications often do not want to (or even cannot) code load balancing and fault tolerance into their programs.
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Chapter and Conference Paper
Evaluation of Multicast Methods to Maintain a Global Name Space for Transparent Process Migration in Workstation Clusters
In this paper we examine the performance and fault tolerance of different multicast based methods for maintaining the consistence of distributed data, depending on the network topology and packet loss probabil...
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Chapter and Conference Paper
Load management for load balancing on heterogeneous platforms: A comparison of traditional and neural network based approaches
In this paper we compare simple load metrics with neural networks which have been trained to predict the expected delay of an application from the sampled load informations. The results show that the proposed ...
