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May 8 – 12, 2023
Norfolk Waterside Marriott
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First implementation and results of the Analysis Grand Challenge with a fully Pythonic RDataFrame

May 9, 2023, 5:15 PM
Hampton Roads Ballroom VIII (Norfolk Waterside Marriott)

Hampton Roads Ballroom VIII

Norfolk Waterside Marriott

235 East Main Street Norfolk, VA 23510
Oral Track 6 - Physics Analysis Tools Track 6 - Physics Analysis Tools


Padulano, Vincenzo Eduardo (CERN)


The growing amount of data generated by the LHC requires a shift in how HEP analysis tasks are approached. Efforts to address this computational challenge have led to the rise of a middle-man software layer, a mixture of simple, effective APIs and fast execution engines underneath. Having common, open and reproducible analysis benchmarks proves beneficial in the development of these modern tools. One such benchmark is provided by the Analysis Grand Challenge (AGC), which represents a blueprint for a realistic analysis pipeline. This contribution presents the first AGC implementation that leverages ROOT RDataFrame, a powerful, modern and scalable execution engine for the HENP use cases. The different steps of the benchmarks are written with a composable, flexible and fully Pythonic API. RDataFrame can then transparently run the computations on all the cores of a machine or on multiple nodes thanks to automatic dataset splitting and transparent workload distribution. The portability of this implementation is shown by running on various resources, from managed facilities to open cloud platforms for research, showing usage of interactive and distributed environments.

Consider for long presentation No

Primary authors

Padulano, Vincenzo Eduardo (CERN) Dr Guiraud, Enrico (CERN) Mr Falko, Andrii (Taras Shevchenko National University of Kyiv) Gazzarrini, Elena (CERN) Mr Garcia Garcia, Enrique (CERN) Mr Gosein, Domenic (CERN)

Presentation materials

Peer reviewing