PoS - Proceedings of Science
Volume 397 - The Ninth Annual Conference on Large Hadron Collider Physics (LHCP2021) - Poster Session
Hyperloop – The ALICE analysis train system for Run 3
R. Quishpe*, J.F. Grosse-oetringhaus, R. Cruceru and C. Grigoras
Full text: pdf
Pre-published on: October 20, 2021
Published on: November 17, 2021
Abstract
ALICE analyses mostly deal with large datasets using the distributed Grid infrastructure. In LHC running periods 1 and 2, ALICE developed a system of analysis trains (so-called “LEGO trains”) that allowed the user to configure analysis tasks (called wagons) that run on the same data. The LEGO train system builds upon existing tools: the ALICE analysis framework as well as the Grid submission and monitoring infrastructure. This centralized system improved the resource utilization and provided a graphical user interface (UI), in addition to bookkeeping functionalities. Currently, 90$\%$ of ALICE analyses use the train system. The ongoing major upgrade for LHC Run 3 will enable the experiment to cope with an increase of Pb-Pb collision data of two orders of magnitude compared to the Run 1 and 2 data-taking periods. In order to process this unprecedented data sample, a new computing model has been implemented, the Online-Offline Computing System (O$^{2}$). Analysis trains will also be the main workhorse for analysis in Run 3: a new infrastructure, Hyperloop, is being developed based on the successful concept of the LEGO trains. The Hyperloop train system includes a different and improved UI using modern responsive web tools, bookkeeping, instantaneous automatic testing, and the production of derived skimmed data. So far, about 800 Hyperloop trains have been successfully submitted to the Grid and ALICE analysis facilities using converted Run 2 data. An overview of the ALICE train system concept is given, highlighting the improvements of the new Hyperloop framework for analysis in Run 3.
DOI: https://doi.org/10.22323/1.397.0250
How to cite

Metadata are provided both in "article" format (very similar to INSPIRE) as this helps creating very compact bibliographies which can be beneficial to authors and readers, and in "proceeding" format which is more detailed and complete.

Open Access
Creative Commons LicenseCopyright owned by the author(s) under the term of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.