Speaker
Dr
Sami Kama
(Southern Methodist University (US))
Description
The growing size and complexity of events produced at the high luminosities expected in 2015 at the Large Hadron Collider demands much more computing power for the online event selection and for the offline data reconstruction than in the previous data taking period. In recent years, the explosive performance growth of low-cost, massively parallel processors like Graphical Processing Units (GPUs) - both in computing power and in low energy consumption - make GPUs extremely attractive for solving the challenging computing tasks of high energy physics experiment like ATLAS.
After the optimisation of the computing intensive algorithms and their adaptation to GPUs, thus exploiting the paradigm of massively parallel computing, a small scale prototype of the full reconstruction chain of the ATLAS High Level Trigger under inclusion of the GPU-based algorithms has been implemented. We discuss the integration procedure of this prototype, the achieved performance and the prospects for the future.
Primary author
Dr
Sami Kama
(Southern Methodist University (US))
Co-authors
Ademar Tavares Delgado
(LIP Laboratorio de Instrumentacao e Fisica Experimental de Part)
Andrea Messina
(Universita e INFN, Roma I)
Antonio Sidoti
(INFN Bologna (IT))
Dmitry Emeliyanov
(STFC - Rutherford Appleton Lab. (GB))
John Baines
(STFC - Rutherford Appleton Lab. (GB))
Prof.
Jose Soares Augusto
(LIP/FCUL)
Lorenzo Rinaldi
(Universita e INFN (IT))
Lourenco Vaz Gil Lopes
(LIP Laboratorio de Instrumentacao e Fisica Experimental de Part)
Matteo Bauce
(Universita e INFN, Roma I (IT))
Matteo Negrini
(Universita e INFN (IT))
Dr
Patricia Conde Muino
(LIP Laboratorio de Instrumentacao e Fisica Experimental de Part)
Ricardo Jose Morais Silva Goncalo
(LIP Laboratorio de Instrumentacao e Fisica Experimental de Part)
Dr
Salvatore Tupputi
(Universita e INFN, Bologna (IT))
Tomasz Bold
(AGH Univ. of Science and Technology, Krakow)
