The Climate-G testbed: towards large scale distributed data management for climate change

Climate-G is a large scale distributed testbed devoted to climate change research. It is an unfunded effort started in 2008 and involving a wide community both in Europe and US. The testbed is an interdisciplinary effort involving partners from several institutions and joining expertise in the field of climate change and computational science. Its main goal is to allow scientists carrying out geographical and cross-institutional data discovery, access, analysis, visualization and sharing of climate data. It represents an attempt to address, in a real environment, challenging data and metadata management issues. This paper presents a complete overview about the Climate-G testbed highlighting the most important results that have been achieved since the beginning of this project

VERCE delivers a productive e-Science environment for seismology research

The VERCE project has pioneered an e-Infrastructure to support researchers using established simulation codes on high-performance computers in conjunction with multiple sources of observational data. This is accessed and organised via the VERCE science gateway that makes it convenient for seismologists to use these resources from any location via the Internet. Their data handling is made flexible and scalable by two Python libraries, ObsPy and dispel4py and by data services delivered by ORFEUS and EUDAT. Provenance driven tools enable rapid exploration of results and of the relationships between data, which accelerates understanding and method improvement. These powerful facilities are integrated and draw on many other e-Infrastructures. This paper presents the motivation for building such systems, it reviews how solid-Earth scientists can make significant research progress using them and explains the architecture and mechanisms that make their construction and operation achievable. We conclude with a summary of the achievements to date and identify the crucial steps needed to extend the capabilities for seismologists, for solid-Earth scientists and for similar disciplines.Comment: 14 pages, 3 figures. Pre-publication version of paper accepted and published at the IEEE eScience 2015 conference in Munich with substantial additions, particularly in the analysis of issue

The cloud4health Project. Secondary use of clinical data with secure cloud-based text mining services

Advances in translational and personalized medicine require the integration of multiple patient related resources across different organizational bodies. Thus, secure cloud environments for huge data processing, storage and data integration are needed. Moreover, the integration of clinical patient data is indispensable for translational research. Although operational e-health record systems are established in most hospitals, many clinical and phenotypically relevant parameters can only be found in unstructured texts like medical records and reports. To meet these challenges, the cloud4health project established a cloud-based text mining platform to facilitate information extraction of biomedical texts in a secure cloud environment. In order to comply with privacy regulations, general tech nical demands and security rules for such a cloud installation were developed and have been implemented. Different clinical use cases show the wide spectrum of application of specific text mining services in a secure cloud environment. As application examples, two use cases utilizing text mining technologies to analyse pathology and surgery reports are analysed in detail

Access climate data in ESG from the EGI infrastructure

Access climate data in ESG from the EGI infrastructur

Cooling Circuit Simulation II: A Numerical Example

Cooling as well as heating circuits can be modeled as a network of elements that obey mass, momentum, and energy balance laws. Typical elements in such circuits are pipes, regulated pumps, regulated (multi-way) valves, and energy exchangers. Since cooling or heating can need a lot of energy, one is interested in understanding, reducing, and re-using energy flows. Supercomputing centers provide one important class of applications here. This article provides a detailed case study of a real system for which measurements and technical data are available. We briefly discuss our overall MYNTS framework for modeling, simulation, and optimization of such circuits. In more detail, we explain by means of a case study how we obtain and combine the network topology, element characteristics, and measurement data in order to set up and validate simulation models. Numerical results are presented and discussed. The case study is complemented in Clees et al. (Cooling Circuit Simulation I: Modeling. Springer, Berlin, 2017) (see pages 61--79 in this book) by a general introduction to the underlying physical model and its numerical treatment

A roadmap for a dedicated Earth Science Grid platform

Due to its intensive data processing and highly distributed organization, the multidisciplinary Earth Science applications community is uniquely positioned for the uptake and exploitation of Grid technologies. Currently Enabling Grids for E-sciencE, and other large Grid infrastructures are already deployed and capable of operational services. So far however, the adoption and exploitation of Grid technology throughout the Earth Science community has been slower than expected. The Dissemination and Exploitation of GRids in Earth sciencE project, proposed by the European Commission to assist and accelerate this process in a number of different ways, had between its main goals the creation of a roadmap towards Earth Science Grid platform. This paper presents the resulting roadmap

Increasing data center energy efficiency via simulation and optimization of cooling circuits - a practical approach

The steady rise in energy consumption by data centers world wide over the last decade and the future 20 MW exascale-challenge in High Performance Computing (HPC) makes saving energy an important consideration for HPC data centers. A move from air-cooled HPC systems to indirect or direct water-cooled systems allowed for the use of chiller-less cold or hot water cooling. However, controlling such systems needs special attention in order to arrive at an optimal compromise of low energy consumption and robust operating conditions. This paper highlights a newly developed concept along with software tools for modeling the data center cooling circuits, collecting data, and simulating and analyzing operating conditions. A first model for the chiller-less cooling loop of the Leibniz Supercomputing Center (LRZ) will be presented and lessons learned will be discussed, demonstrating the possibilities offered by the new concept and tools

VERCE delivers a productive e-science environment for seismology research

The VERCE project has pioneered an e-Infrastructure to support researchers using established simulation codes on high-performance computers in conjunction with multiple sources of observational data. This is accessed and organised via the VERCE science gateway that makes it convenient for seismologists to use these resources from any location via the Internet. Their data handling is made flexible and scalable by two Python libraries, ObsPy and dispel4py and by data services delivered by ORFEUS and EUDAT. Provenance driven tools enable rapid exploration of results and of the relationships between data, which accelerates understanding and method improvement. These powerful facilities are integrated and draw on many other e-Infrastructures. This paper presents the motivation for building such systems, it reviews how solid-Earth scientists can make significant research progress using them and explains the architecture and mechanisms that make their construction and operation achievable. We conclude with a summary of the achievements to date and identify the crucial steps needed to extend the capabilities for seismologists, for solid-Earth scientists and for similar disciplines.</p