EPJ Web Conf.
Volume 245, 202024th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2019)
|Number of page(s)||9|
|Section||3 - Middleware and Distributed Computing|
|Published online||16 November 2020|
New developments in cost modeling for the LHC computing
Univ. Grenoble Alpes, CNRS, Grenoble INP, LPSC-IN2P3, Grenoble, France
2 INFN Sezione di Pisa, Pisa, Italy
3 INFN Sezione di Bologna, Università di Bologna, Bologna, Italy
4 European Organisation for Nuclear Research (CERN), Geneva, Switzerland
5 Università e INFN, Ferrara, Ferrara, Italy
6 Department of Physics and Astronomy, University of Sheffield, Sheffield, United Kingdom
7 Physics Department, Brookhaven National Laboratory, Upton, NY, USA
8 Centre de Calcul de l’IN2P3 du CNRS, Lyon, France
9 Centro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid, Spain
10 LAL, Université Paris-Sud and CNRS/IN2P3, Orsay, France
11 Deutsches Elektronen-Synchrotron, Hamburg, Germany
12 Princeton University, Princeton, NJ, USA
13 Università degli Studi di Milano-Bicocca, Milano, Italy
14 INFN Sezione di Padova, Università di Padova, Padova, Italy
15 SUPA School of Physics and Astronomy, University of Glasgow, Glasgow, United Kingdom
16 STFC Rutherford Appleton Laboratory, Didcot, United Kingdom
17 Laboratoire Leprince-Ringuet, Ecole Polytechnique, CNRS/IN2P3, Université Paris-Saclay, Palaiseau, France
18 Lunds Universitet, Fysiska Institutionen, Avdelningen för Experimentell Högenergifysik, Box 118, 221 00 Lund, Sweden
19 University of California, San Diego, La Jolla, CA, USA
* e-mail: Andrea.Sciaba@cern.ch
Published online: 16 November 2020
The increase in the scale of LHC computing during Run 3 and Run 4 (HL-LHC) will certainly require radical changes to the computing models and the data processing of the LHC experiments. The working group established by WLCG and the HEP Software Foundation to investigate all aspects of the cost of computing and how to optimise them has continued producing results and improving our understanding of this process. In particular, experiments have developed more sophisticated ways to calculate their resource needs, we have a much more detailed process to calculate infrastructure costs. This includes studies on the impact of HPC and GPU based resources on meeting the computing demands. We have also developed and perfected tools to quantitatively study the performance of experiments workloads and we are actively collaborating with other activities related to data access, benchmarking and technology cost evolution. In this contribution we expose our recent developments and results and outline the directions of future work.
© The Authors, published by EDP Sciences, 2020
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.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.