Use of hardware accelerators for ATLAS computing

Bauce, Matteo; Dankel, Maik; Boeing, Rene; Howard, Jacob; Kama, Sami; ATLAS Collaboration

doi:10.3204/DESY-PROC-2014-05/10

Contribution to a conference proceedings/Internal Report

PUBDB-2015-05324

Use of hardware accelerators for ATLAS computing

Bauce, M. ; Boeing, R. ; Dankel, M. ; Howard, J. ; Kama, S. ; ATLAS Collaboration (Collaboration author)DESY*

2015
Deutsches Elektronen-Synchrotron, DESY Hamburg

GPU Computing in High-Energy Physics, GPUHEP2014, Pisa, Italy, 10 Sep 2014 - 12 Sep 2014 Hamburg : Deutsches Elektronen-Synchrotron, DESY 48-54 (2015) [10.3204/DESY-PROC-2014-05/10]

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Please use a persistent id in citations: doi:10.3204/DESY-PROC-2014-05/10

Report No.: DESY-PROC-2014-05

Abstract: 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 parallel processing and has to include the use of co-processors. However, since the design of most of the 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 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 the multiple process based Athena framework using the Accelerator Process Extension APE

Keyword(s): programming ; ATLAS ; hardware ; acceleration ; microprocessor ; multiprocessor: graphics ; data management