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Recent experience and future evolution of the CMS High Level Trigger System

The CMS experiment at the LHC uses a two-stage trigger system, with events flowing from the first level trigger at a rate of 100 kHz. These events are read out by the Data Acquisition system (DAQ), assembled in memory in a farm of computers, and finally fed into the high-level trigger (HLT) software...

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Detalles Bibliográficos
Autores principales: Bauer, Gerry, Behrens, Ulf, Branson, James, Bukowiec, Sebastian Czeslaw, Chaze, Olivier, Cittolin, Sergio, Coarasa Perez, Jose Antonio, Deldicque, Christian, Dobson, Marc, Dupont, Aymeric, Erhan, Samim, Gigi, Dominique, Glege, Frank, Gomez-Reino Garrido, Robert, Hartl, Christian, Holzner, Andre Georg, Masetti, Lorenzo, Meijers, Franciscus, Meschi, Emilio, Mommsen, Remigius, Nunez Barranco Fernandez, Carlos, O'Dell, Vivian, Orsini, Luciano, Paus, Christoph Maria Ernst, Petrucci, Andrea, Pieri, Marco, Polese, Giovanni, Racz, Attila, Raginel, Olivier, Sakulin, Hannes, Sani, Matteo, Schwick, Christoph, Spataru, Andrei Cristian, Stoeckli, Fabian, Sumorok, Konstanty
Lenguaje:eng
Publicado: 2012
Materias:
Acceso en línea:http://cds.cern.ch/record/1461735
Descripción
Sumario:The CMS experiment at the LHC uses a two-stage trigger system, with events flowing from the first level trigger at a rate of 100 kHz. These events are read out by the Data Acquisition system (DAQ), assembled in memory in a farm of computers, and finally fed into the high-level trigger (HLT) software running on the farm. The HLT software selects interesting events for offline storage and analysis at a rate of a few hundred Hz. The HLT algorithms consist of sequences of offline-style reconstruction and filtering modules, executed on a farm of 0(10000) CPU cores built from commodity hardware. Experience from the 2010-2011 collider run is detailed, as well as the current architecture of the CMS HLT, and its integration with the CMS reconstruction framework and CMS DAQ. The short- and medium-term evolution of the HLT software infrastructure is discussed, with future improvements aimed at supporting extensions of the HLT computing power, and addressing remaining performance and maintenance issues.