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Boosting RDataFrame performance with transparent bulk event processing / Guiraud, Enrico (CERN) ; Blomer, Jakob (CERN) ; Canal, Philippe (Fermilab) ; Naumann, Axel (CERN)
RDataFrame is ROOT’s high-level interface for Python and C++ data analysis. Since it first became available, RDataFrame adoption has grown steadily and it is now poised to be a major component of analysis software pipelines for LHC Run 3 and beyond. [...]
FERMILAB-CONF-24-0684-CSAID.- 2024 - 8 p. - Published in : EPJ Web Conf. 295 (2024) 06006 Fulltext: 3afc9b57f03c0d303680c14cbbcb8c23 - PDF; document - PDF; External link: Fermilab Library Server
In : 26th International Conference on Computing in High Energy & Nuclear Physics, Norfolk, Virginia, Us, 8 - 12 May 2023, pp.06006

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(91)

Leveraging HPC resources with distributed RDataFrame / Padulano, V E (CERN ; Valencia, Polytechnic U.) ; Kabadzhov, I D (CERN ; Freiburg U., Inst. Phys. Chem.) ; Saavedra, E T (CERN) ; Guiraud, E (CERN)
The declarative approach to data analysis provides high-level abstractions for users to operate on their datasets in a much more ergonomic fashion compared to imperative interfaces. ROOT offers such a tool with RDataFrame, which has been tested in production environments and used in real-world analyses with optimal results. [...]
2023 - 5 p. - Published in : J. Phys. : Conf. Ser. 2438 (2023) 012097 Fulltext: PDF;
In : 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2021), Daejeon, Korea, 29 Nov - 3 Dec 2021, pp.012097

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(73)

Leveraging an open source serverless framework for high energy physics computing / Padulano, Vincenzo Eduardo (Valencia, Polytechnic U. ; CERN) ; Cortés, Pablo Oliver (Valencia, Polytechnic U.) ; Alonso‑Jordá, Pedro (Valencia, Polytechnic U.) ; Saavedra, Enric Tejedor (CERN) ; Risco, Sebastián (Valencia, Polytechnic U.) ; Moltó, Germán (Valencia, Polytechnic U.)
CERN (Centre Europeen pour la Recherce Nucleaire) is the largest research centre for high energy physics (HEP). It offers unique computational challenges as a result of the large amount of data generated by the large hadron collider. [...]
2023 - 26 p. - Published in : J. Supercomput. 79 (2023) 8940-8965 Fulltext: PDF;

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(70)

Introducing Live Visualization for Distributed RDataFrame with Dask / Taider, Silia
ROOT is a powerful data analysis framework for High Energy Physics providing the users with a wide range of tools, namely RDataFrame, a high-level interface for data analysis. [...]
CERN-STUDENTS-Note-2023-159. - 2023
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(69)

Using RDataFrame, ROOT’s declarative analysis tool, in a CMS physics study / Manca, Elisabetta (speaker) (INFN Sezione di Pisa, Universita' e Scuola Normale Superiore, P) ; Guiraud, Enrico (speaker) (CERN, University of Oldenburg (DE))
With the expected large increase in the amount of available data in LHC Run 3, now more than ever HEP scientists must be able to efficiently write robust, performant analysis software that can take full advantage of the underlying hardware. Multicore computing resources are commonplace, and current trends in scientific computing include increased availability of manycore architectures. [...]
2019 - 4486. EP Software Seminar External link: Event details In : Using RDataFrame, ROOT’s declarative analysis tool, in a CMS physics study

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(67)

RDataFrame enhancements for HEP analyses / Guiraud, E (CERN) ; Blomer, J (CERN) ; Hageboeck, S (CERN) ; Naumann, A (CERN) ; Padulano, V E (CERN) ; Tejedor, E (CERN) ; Wunsch, S (CERN)
In recent years, RDataFrame, ROOT’s high-level interface for data analysis and processing, has seen widespread adoption on the part of HEP physicists. Much of this success is due to RDataFrame’s ergonomic programming model that enables the implementation of common analysis tasks more easily than previous APIs, without compromising on application performance. [...]
2023 - 6 p. - Published in : J. Phys. : Conf. Ser. 2438 (2023) 012116 Fulltext: PDF;
In : 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2021), Daejeon, Korea, 29 Nov - 3 Dec 2021, pp.012116

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(57)

Distributed data analysis with ROOT RDataFrame / Padulano, Vincenzo Eduardo (CERN ; Milan Bicocca U.) ; Villanueva, Javier Cervantes (CERN) ; Guiraud, Enrico (CERN ; Oldenburg U.) ; Tejedor Saavedra, Enric (CERN)
Widespread distributed processing of big datasets has been around for more than a decade now thanks to Hadoop, but only recently higher-level abstractions have been proposed for programmers to easily operate on those datasets, e.g. Spark. [...]
2020 - 7 p. - Published in : EPJ Web Conf. 245 (2020) 03009 Fulltext from publisher: PDF;
In : 24th International Conference on Computing in High Energy and Nuclear Physics, Adelaide, Australia, 4 - 8 Nov 2019, pp.03009

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(57)

RDataFrame: Easy parallel ROOT analysis at 100 threads / Piparo, Danilo (CERN) ; Canal, Philippe (Fermilab) ; Guiraud, Enrico (CERN ; Carl von Ossietzky U., Oldenburg (main)) ; Valls Pla, Xavier (CERN) ; Ganis, Gerardo (CERN) ; Amadio, Guilherme (CERN) ; Naumann, Axel (CERN) ; Tejedor, Enric (CERN)
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. [...]
FERMILAB-CONF-19-550-SCD.- 2019 - 8 p. - Published in : EPJ Web Conf. 214 (2019) 06029 Fulltext from publisher: PDF;
In : 23rd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2018, Sofia, Bulgaria, 9 - 13 Jul 2018, pp.06029

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(44)

Enhancements to declarative analysis in ROOT / Tumolo, Massimo
ROOT is a tool used by virtually every High Energy Physics analysis inside and outside CERN, thanks to the range of functionalities offered. [...]
CERN-STUDENTS-Note-2018-090. - 2018
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Fine-grained data caching approaches to speedup a distributed RDataFrame analysis / Padulano, Vincenzo Eduardo (Valencia, Polytechnic U. ; CERN) ; Tejedor Saavedra, Enric (CERN) ; Alonso-Jordá, Pedro (Valencia, Polytechnic U.)
Thanks to its RDataFrame interface, ROOT now supports the execution of the same physics analysis code both on a single machine and on a cluster of distributed resources. In the latter scenario, it is common to read the input ROOT datasets over the network from remote storage systems, which often increases the time it takes for physicists to obtain their results. [...]
2021 - 11 p. - Published in : EPJ Web Conf. 251 (2021) 02027 Fulltext: PDF;
In : 25th International Conference on Computing in High-Energy and Nuclear Physics (CHEP), Online, Online, 17 - 21 May 2021, pp.02027

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