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Frameworks to monitor and predict rates and resource usage in the ATLAS High Level Trigger

The ATLAS High Level Trigger Farm consists of around 40,000 CPU cores which filter events at an input rate of up to 100 kHz. A costing framework is built into the high level trigger thus enabling detailed monitoring of the system and allowing for data-driven predictions to be made utilising speciali...

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Detalles Bibliográficos
Autor principal: Martin, Tim
Lenguaje:eng
Publicado: 2016
Materias:
Acceso en línea:https://dx.doi.org/10.1088/1742-6596/898/3/032007
http://cds.cern.ch/record/2239816
Descripción
Sumario:The ATLAS High Level Trigger Farm consists of around 40,000 CPU cores which filter events at an input rate of up to 100 kHz. A costing framework is built into the high level trigger thus enabling detailed monitoring of the system and allowing for data-driven predictions to be made utilising specialist datasets. An overview is presented in to how ATLAS collects in-situ monitoring data on CPU usage during the trigger execution, and how these data are processed to yield both low level monitoring of individual selection-algorithms and high level data on the overall performance of the farm. For development and prediction purposes, ATLAS uses a special ‘Enhanced Bias’ event selection. This mechanism is explained along with how it is used to profile expected resource usage and output event rate of new physics selections, before they are executed on the actual high level trigger farm.