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- ZIB Allgemein (6) (remove)
In Analogie zu den Elektrizitätsnetzen electricity grid), von denen die technische Revolution ausging, wurde der Begriff Computational Grid (kurz Grid) geprägt. Ein wichtiger Bestandteil des Systems liegt im benutzerfreundlichen Zugang und der koordinierten Nutzung der weltweit verteilten Speicherressourcen und Rechnerkapazitäten. Bei der Entwicklung dazu notwendiger Technologien und Software (Middleware) profitiert man von Kenntnissen und Erfahrungen bei der Entwicklung verteilter Algorithmen, dem Software-Engineering und dem Supercomputing.
\textsf{\itshape{GuiGen}} is a comprehensive set of tools for creating customized graphical user interfaces (GUIs). It draws from the concept of computing portals, which are here seen as interfaces to application-specific computing services for user communities. While \textsf{\itshape{GuiGen}} was originally designed for the use in computational grids, it can be used in client/server environments as well. Compared to other GUI generators, \textsf{\itshape{GuiGen}} is more versatile and more portable. It can be employed in many different application domains and on different target platforms. With \textsf{\itshape{GuiGen}}, application experts (rather than computer scientists) are able to create their own individually tailored GUIs.
Global grid environments do not only provide massive aggregated computing power but also an unprecedented amount of distributed storage space. Unfortunately, dynamic changes caused by component failures, local decisions, and irregular data updates make it difficult to efficiently use this capacity. In this paper, we address the problem of improving data availability in the presence of unreliable components. We present an analytical model for determining an optimal combination of distributed replica catalogs, catalog sizes, and replica servers. Empirical simulation results confirm the accuracy of our theoretical analysis. Our model captures the characteristics of highly dynamic environments like peer-to-peer networks, but it can also be applied to more centralized, less dynamic grid environments like the European {\em DataGrid}.
The success of large-scale multi-national projects like the forthcoming analysis of the LHC particle collision data at CERN relies to a great extent on the ability to efficiently utilize computing a management software (Datagrid, Globus, etc.), while the effective integration of computing nodes has been largely neglected up to now. This is the focus of our work. We present a framework for a high-performance cluster that can be used as a reliable computing node in the Grid. We outline the cluster architecture, the management of distributed data and the seamless intergration of the cluster into the Grid environment.
Workstation clusters are often not only used for high-throughput computing in time-sharing mode but also for running complex parallel jobs in space-sharing mode. This poses several difficulties to the resource management system, which must be able to reserve computing resources for exclusive use and also to determine an optimal process mapping for a given system topology. On the basis of our CCS software, we describe the anatomy of a modern resource management system. Like Codine, Condor, and LSF, CCS provides mechanisms for the user-friendly system access and management of clusters. But unlike them, CCS is targeted at the effective support of space-sharing parallel and even metacomputers. Among other features, CCS provides a versatile resource description facility, topology-based process mapping, pluggable schedulers, and hooks to metacomputer management.
Power-User und Supercomputer
(1999)