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Title: RDataFrame: Easy Parallel ROOT Analysis at 100 Threads

Abstract

The Physics programmes of LHC Run III and HL-LHC challenge the HEP community. The volume of data to be handled is unprecedented at every step of the data processing chain: analysis is no exception. Physicists must be provided with first-class analysis tools which are easy to use, exploit bleeding edge hardware technologies and allow to seamlessly express parallelism. This document discusses the declarative analysis engine of ROOT, RDataFrame, and gives details about how it allows to profitably exploit commodity hardware as well as high-end servers and manycore accelerators thanks to the synergy with the existing parallelised ROOT components. Real-life analyses of LHC experiments’ data expressed in terms of RDataFrame are presented, highlighting the programming model provided to express them in a concise and powerful way. The recent developments which make RDataFrame a lightweight data processing framework are described, such as callbacks and I/O capabilities. Finally, the flexibility of RDataFrame and its ability to read data formats other than ROOT’s are characterised, as an example it is discussed how RDataFrame can directly read and analyse LHCb’s raw data format MDF.

Authors:
 [1]; ORCiD logo [2];  [3];  [1];  [1];  [1];  [1];  [1]
  1. European Organization for Nuclear Research (CERN), Geneva (Switzerland)
  2. Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
  3. European Organization for Nuclear Research (CERN), Geneva (Switzerland); Univ. of Oldenburg, Oldenburg (Germany)
Publication Date:
Research Org.:
Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
OSTI Identifier:
1574960
Report Number(s):
FERMILAB-CONF-19-550-SCD
Journal ID: ISSN 2100-014X; oai:inspirehep.net:1761291
Grant/Contract Number:  
AC02-07CH11359
Resource Type:
Accepted Manuscript
Journal Name:
EPJ Web of Conferences
Additional Journal Information:
Journal Volume: 214; Conference: 23. International Conference on Computing in High Energy and Nuclear Physics, Sofia (Bulgaria), 9-13 Jul 2018; Journal ID: ISSN 2100-014X
Publisher:
EDP Sciences
Country of Publication:
United States
Language:
English
Subject:
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Citation Formats

Piparo, Danilo, Canal, Philippe, Guiraud, Enrico, Pla, Xavier Valls, Ganis, Gerardo, Amadio, Guilherme, Naumann, Axel, and Tejedor, Enric. RDataFrame: Easy Parallel ROOT Analysis at 100 Threads. United States: N. p., 2019. Web. doi:10.1051/epjconf/201921406029.
Piparo, Danilo, Canal, Philippe, Guiraud, Enrico, Pla, Xavier Valls, Ganis, Gerardo, Amadio, Guilherme, Naumann, Axel, & Tejedor, Enric. RDataFrame: Easy Parallel ROOT Analysis at 100 Threads. United States. doi:10.1051/epjconf/201921406029.
Piparo, Danilo, Canal, Philippe, Guiraud, Enrico, Pla, Xavier Valls, Ganis, Gerardo, Amadio, Guilherme, Naumann, Axel, and Tejedor, Enric. Tue . "RDataFrame: Easy Parallel ROOT Analysis at 100 Threads". United States. doi:10.1051/epjconf/201921406029. https://www.osti.gov/servlets/purl/1574960.
@article{osti_1574960,
title = {RDataFrame: Easy Parallel ROOT Analysis at 100 Threads},
author = {Piparo, Danilo and Canal, Philippe and Guiraud, Enrico and Pla, Xavier Valls and Ganis, Gerardo and Amadio, Guilherme and Naumann, Axel and Tejedor, Enric},
abstractNote = {The Physics programmes of LHC Run III and HL-LHC challenge the HEP community. The volume of data to be handled is unprecedented at every step of the data processing chain: analysis is no exception. Physicists must be provided with first-class analysis tools which are easy to use, exploit bleeding edge hardware technologies and allow to seamlessly express parallelism. This document discusses the declarative analysis engine of ROOT, RDataFrame, and gives details about how it allows to profitably exploit commodity hardware as well as high-end servers and manycore accelerators thanks to the synergy with the existing parallelised ROOT components. Real-life analyses of LHC experiments’ data expressed in terms of RDataFrame are presented, highlighting the programming model provided to express them in a concise and powerful way. The recent developments which make RDataFrame a lightweight data processing framework are described, such as callbacks and I/O capabilities. Finally, the flexibility of RDataFrame and its ability to read data formats other than ROOT’s are characterised, as an example it is discussed how RDataFrame can directly read and analyse LHCb’s raw data format MDF.},
doi = {10.1051/epjconf/201921406029},
journal = {EPJ Web of Conferences},
number = ,
volume = 214,
place = {United States},
year = {2019},
month = {9}
}

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Works referenced in this record:

A Large Hadron Electron Collider at CERN Report on the Physics and Design Concepts for Machine and Detector
journal, July 2012

  • Abelleira Fernandez, J. L.; Adolphsen, C.; Akay, A. N.
  • Journal of Physics G: Nuclear and Particle Physics, Vol. 39, Issue 7
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