Norbert Podhorszki

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Computational science is paramount to the understanding of underlying processes in internal combustion engines of the future that will utilize non-petroleum-based alternative fuels, including carbon-neutral biofuels, and burn in new combustion regimes that will attain high efficiency while minimizing emissions of particulates and nitrogen oxides.(More)
Scientific codes are all subject to variation in performance depending on the runtime platform and/or configuration, the output writing API employed, and the file system for output. Since changing the IO routines to match the optimal or desired configuration for a given system can be costly in terms of human time and machine resources, the Adaptable IO(More)
P-GRADE provides a high-level graphical environment to develop parallel applications transparently both for parallel systems and the Grid. P-GRADE supports the interactive execution of parallel programs as well as the creation of a Condor, Condor-G or Globus job to execute parallel programs in the Grid. In P-GRADE, the user can generate either PVM or MPI(More)
We have developed and implemented the Relational Grid Monitoring Architecture (R-GMA) as part of the DataGrid project, to provide a flexible information and monitoring service for use by other middleware components and applications. R-GMA presents users with a virtual database and mediates queries posed at this database: users pose queries against a global(More)
Peta-scale scientific applications running on High End Computing (HEC) platforms can generate large volumes of data. For high performance storage and in order to be useful to science end users, such data must be organized in its layout, indexed, sorted, and otherwise manipulated for subsequent data presentation, visualization, and detailed analysis. In(More)
The first Provenance Challenge was set up in order to provide a forum for the community to understand the capabilities of different provenance systems and the expressiveness of their provenance representations. To this end, a functional magnetic resonance imaging workflow was defined, which participants had to either simulate or run in order to produce some(More)
Luc Moreau∗, Bertram Ludäscher, Ilkay Altintas, Roger S. Barga, Shawn Bowers, Steven Callahan, George Chin Jr., Ben Clifford, Shirley Cohen, Sarah Cohen-Boulakia, Susan Davidson, Ewa Deelman, Luciano Digiampietri, Ian Foster, Juliana Freire, James Frew, Joe Futrelle, Tara Gibson, Yolanda Gil, Carole Goble, Jennifer Golbeck, Paul Groth, David A. Holland,(More)
GRM was originally designed and implemented as part of the P-GRADE graphical parallel program development environment running on supercomputers and clusters. In the framework of the biggest European Grid project, the DataGrid we investigated the possibility of transforming GRM to a grid application monitoring infrastructure. This paper presents the(More)
We introduce and describe scientific workflows, i.e., executable descriptions of automatable scientific processes such as computational science simulations and data analyses. Scientific workflows are often expressed in terms of tasks and their (dataflow) dependencies. This chapter first provides an overview of the characteristic features of scientific(More)