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Distributed analysis environment for HEP and interdisciplinary applications
Huge data volumes of Large Hadron Collider experiments require parallel end-user analysis on clusters of hundreds of machines. While the focus of end-user High-Energy Physics analysis is on ntuples, the master-worker model of parallel processing may be also used in other contexts such as detector si...
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Lenguaje: | eng |
Publicado: |
2003
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1016/S0168-9002(03)00459-5 http://cds.cern.ch/record/624983 |
Sumario: | Huge data volumes of Large Hadron Collider experiments require parallel end-user analysis on clusters of hundreds of machines. While the focus of end-user High-Energy Physics analysis is on ntuples, the master-worker model of parallel processing may be also used in other contexts such as detector simulation. The aim of DIANE R&D project (http://cern.ch/it-proj-diane) currently held by CERN IT/API group is to create a generic, component-based framework for distributed, parallel data processing in master-worker model. Pre-compiled user analysis code is loaded dynamically at runtime in component libraries and called back when appropriate. Such application-oriented framework must be flexible enough to integrate with the emerging GRID technologies as they become available in the time to come. Therefore, common services such as environment reconstruction, code distribution, load balancing and authentication are designed and implemented as pluggable modules. This approach allows to easily replace them with modules implemented with newer technology as necessary. The paper gives an overview of DIANE architecture and explains the main design choices. Selected examples of diverse applications from a variety of domains applicable to DIANE are presented. As well as preliminary benchmarking results. |
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