| Issue |
EPJ Web Conf.
Volume 251, 2021
25th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2021)
|
|
|---|---|---|
| Article Number | 03063 | |
| Number of page(s) | 7 | |
| Section | Offline Computing | |
| DOI | https://doi.org/10.1051/epjconf/202125103063 | |
| Published online | 23 August 2021 | |
https://doi.org/10.1051/epjconf/202125103063
ALICE Run 3 Analysis Framework
1 Organisation Européenne pour la Recherche Nucléaire, CERN, Meyrin, Switzerland
2 Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland
* e-mail: anton.alkin@cern.ch
Published online: 23 August 2021
In LHC Run 3 the ALICE Collaboration will have to cope with an increase of lead-lead collision data of two orders of magnitude compared to the Run 1 and 2 data-taking periods. The Online-Offline (O2) software framework has been developed to allow for distributed and efficient processing of this unprecedented amount of data. Its design, which is based on a message-passing back end, required the development of a dedicated Analysis Framework that uses the columnar data format provided by Apache Arrow. The O2 Analysis Framework provides a user-friendly high-level interface and hides the complexity of the underlying distributed framework. It allows the users to access and manipulate the data in the new format both in the traditional “event loop” and a declarative approach using bulk processing operations based on Arrow’s Gandiva sub-project. Building on the well-tested system of analysis trains developed by ALICE in Run 1 and 2, the AliHyperloop infrastructure is being developed. It provides a fast and intuitive user interface for running demanding analysis workflows in the GRID environment and on the dedicated Analysis Facility. In this document, we report on the current state and ongoing developments of the Analysis Framework and of AliHyperloop, highlighting the design choices and the benefits of the new system.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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