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A Parallelised ROOT for Future HEP Data Processing

Piparo, Danilo ; Canal, Philippe ; Amadio, Guilherme ; Guiraud, Enrico ; Naumann, Axel ; Valls, Xavier ; Tejedor, Enric Hristov, P. ; Smirnova, O. ; Betev, L. ; Forti, A. ; Litmaath, M.

EPJ Web of Conferences, 2019-01, Vol.214, p.5033 [Periódico revisado por pares]

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Título:
A Parallelised ROOT for Future HEP Data Processing
Autor: Piparo, Danilo ; Canal, Philippe ; Amadio, Guilherme ; Guiraud, Enrico ; Naumann, Axel ; Valls, Xavier ; Tejedor, Enric
Hristov, P. ; Smirnova, O. ; Betev, L. ; Forti, A. ; Litmaath, M.
Assuntos: Data analysis ; Data processing ; MATHEMATICS AND COMPUTING
É parte de: EPJ Web of Conferences, 2019-01, Vol.214, p.5033
Notas: FERMILAB-CONF-19-551-SCD
AC02-07CH11359
USDOE Office of Science (SC), High Energy Physics (HEP)
Descrição: In the coming years, HEP data processing will need to exploit parallelism on present and future hardware resources to sustain the bandwidth requirements. As one of the cornerstones of the HEP software ecosystem, ROOT embraced an ambitious parallelisation plan which delivered compelling results. In this contribution the strategy is characterised as well as its evolution in the medium term. The units of the ROOT framework are discussed where task and data parallelism have been introduced, with runtime and scaling measurements. We will give an overview of concurrent operations in ROOT, for instance in the areas of I/O (reading and writing of data), fitting / minimization, and data analysis. This paper introduces the programming model and use cases for explicit and implicit parallelism, where the former is explicit in user code and the latter is implicitly managed by ROOT internally.
Editor: Les Ulis: EDP Sciences
Idioma: Inglês

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