Louisiana State University

LSU is a major centre of gravity research in the US: it hosts two theory groups and an experimental group working on gravitational wave detectors. A number of former AEI members moved to LSU in 2003, where Ed Seidel took the position of the director of the Center for Computation and Technology at Louisiana State University. Gabrielle Allen holds a cross-affiliation with the AEI, and our work on binary black hole evolutions is often carried out in collaboration with the members of the NR group in the CCT.

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Sonderforschungsbereich/Transregio 7: Gravitational Wave Astronomy

The Sonderforschungsbereich/Transregio 7, “Gravitational Wave Astronomy”, brings together more than 50 scientists as well as numerous PhD and Masters students to deal foremost with modelling cosmic sources of gravitational radiation, improving detector designs and analyzing gravitational wave signals.

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GridLab logo

GridLab is an EU-funded research project which will develop an easy-to-use, flexible, generic and modular Grid Application Toolkit (GAT), enabling todays applications to make innovative use of global computing resources.
The project is grounded by two principles:

  • the co-development of infrastructure with real applications and user communities, leading to working scenarios
  • the dynamic use of grids, with self-aware simulations adapting to their changing environment

GridLab uses the Cactus toolkit as one of its driver applications to develop grid-enabled software.
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AstroGrid logo
German Astronomy Community Grid (GACG)

The German Astronomy Community Grid (GACG), AstroGrid, is a joint project of major German astronomical research institutes, some computer-science groups involved in grid-specific research, and some high-performance computing centres. It is funded by the German Bundesministerium für Bildung und Forschung (BMBF) as a partner project in the German D-Grid Initiative.
The following goals are being pursued:

  • linking German astronomical research institutes in a unified German organizational structure for distributed, collaborative research by using innovative grid-technology,
  • creating a grid-based infrastructure for German astronomical and astrophysical research, based on the computing network of the participating institutes and computing centres, thus enabling a more effective use of hardware resources,
  • integrating distributed astronomical data archives, and – in the longer term – instruments and experiments, into a common GACG research infrastructure,
  • supporting individual research institutes in the effort to contribute their own resources, data and application software, including their integration into the administrative structure of the GACG, thus facilitating the closer and more fruitful collaboration of smaller university groups with larger astronomical research institutes,
  • a stronger involvement of the German astronomical research community in the rapidly evolving, international activities in this research area.

The AstroGrid uses the Cactus toolkit as one of its driver applications to develop grid-enabled software.
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GriKSL logo

GriKSL is a German Grid Computing project, funded by the DFN-Verein. It is aimed to provide software tools and techniques in order to allow compute-intensive applications – such as Black Hole Cactus simulations – to be run on the Grid.

Specifically, the work packages in this project concentrate on

  • the development of adequate means to generically describe and efficiently handle large-scale, multi-dimensional, hierarchical remote data sets distributed over multiple resources
  • enabling existing visualization tools to access such remote data sets efficiently by using techniques such as partial remote file access, data recombination on-the-fly, and adaptive rendering

The data description and data handling implementations developed by GriKSL directly feed back into the Cactus code. The OpenDX and Amira visualization toolkits as used by the group were extended to analyze large-scale data sets from parallel Cactus simulations executed on the group’s remote computing resources.

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