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Use of hardware accelerators for ATLAS computing

Modern HEP experiments produce tremendous amounts of data. This data is processed by in-house built software frameworks which have lifetimes longer than the detector it- self. Such frameworks were traditionally based on serial code and relied on advances in CPU technologies, mainly clock frequency,...

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Detalles Bibliográficos
Autores principales: Dankel, Maik, Kama, Sami, Howard, Jacob, Bauce, Matteo, Boing, Rene
Lenguaje:eng
Publicado: 2014
Materias:
Acceso en línea:https://dx.doi.org/10.3204/DESY-PROC-2014-05/10
http://cds.cern.ch/record/1970398
Descripción
Sumario:Modern HEP experiments produce tremendous amounts of data. This data is processed by in-house built software frameworks which have lifetimes longer than the detector it- self. Such frameworks were traditionally based on serial code and relied on advances in CPU technologies, mainly clock frequency, to cope with increasing data volumes. With the advent of many-core architectures and GPGPUs this paradigm has to shift to paral- lel processing and has to include the use of co-processors. However, since the design of most existing frameworks is based on the assumption of frequency scaling and predate co-processors, parallelisation and integration of co-processors are not an easy task. The ATLAS experiment is an example of such a big experiment with a big software frame- work called Athena. In this proceedings we will present the studies on parallelisation and co-processor (GPGPU) use in data preparation and tracking for trigger and offline recon- struction as well as their integration into a multiple process based Athena framework.