EPJ Web Conf.
Volume 214, 201923rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|Number of page(s)||7|
|Section||T5 - Software development|
|Published online||17 September 2019|
Evolution of the ALICE Software Framework for Run 3
Organisation Européenne pour la Recherche Nucléaire, CERN,
2 Akademia Górniczo-Hutnicza im. Stanisława Staszica, AGH University of Science and Technology, Kraków, Poland
3 Frankfurt Institute for Advanced Studies, Frankfurt, Germany
4 Johann-Wolfgang-Goethe University, Frankfurt, Germany
5 University of Oslo Oslo, Norway
* e-mail: firstname.lastname@example.org
Published online: 17 September 2019
ALICE is one of the four major LHC experiments at CERN. When the accelerator enters the Run 3 data-taking period, starting in 2021, ALICE expects almost 100 times more Pb-Pb central collisions than now, resulting in a large increase of data throughput. In order to cope with this new challenge, the collaboration had to extensively rethink the whole data processing chain, with a tighter integration between Online and Offline computing worlds. Such a system, code-named ALICE O2, is being developed in collaboration with the FAIR experiments at GSI. It is based on the ALFA framework which provides a generalized implementation of the ALICE High Level Trigger approach, designed around distributed software entities coordinating and communicating via message passing.
We will highlight our efforts to integrate ALFA within the ALICE O2 environment. We analyze the challenges arising from the different running environments for production and development, and conclude on requirements for a flexible and modular software framework. In particular we will present the ALICE O2 Data Processing Layer which deals with ALICE specific requirements in terms of Data Model. The main goal is to reduce the complexity of development of algorithms and managing a distributed system, and by that leading to a significant simplification for the large majority of the ALICE users.
© The Authors, published by EDP Sciences, 2019
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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