Issue |
EPJ Web Conf.
Volume 214, 2019
23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|
|
---|---|---|
Article Number | 03027 | |
Number of page(s) | 8 | |
Section | T3 - Distributed computing | |
DOI | https://doi.org/10.1051/epjconf/201921403027 | |
Published online | 17 September 2019 |
https://doi.org/10.1051/epjconf/201921403027
Modeling and Simulation of Load Balancing Strategies for Computing in High Energy Physics
1
Institute for Experimental Particle Physics (ETP)
2
Institute for Program Structures and Data Organization (IPD) at Karlsruhe Institute of Technology (KIT),
Karlsruhe
Germany
* e-mail: rene.caspart@cern.ch
** e-mail: patrick.firnkes@student.kit.edu
*** e-mail: manuel.giffels@cern.ch
**** e-mail: koziolek@kit.edu
† e-mail: g.quast@kit.edu
‡ e-mail: reussner@kit.edu
§ e-mail: mail@mxsg.de
Published online: 17 September 2019
The amount of data to be processed by experiments in high energy physics (HEP) will increase tremendously in the coming years. To cope with this increasing load, most efficient usage of the resources is mandatory. Furthermore, the computing resources for user jobs in HEP will be increasingly distributed and heterogeneous, resulting in more difficult scheduling due to the increasing complexity of the system. We aim to create a simulation for the WLCG helping the HEP community to solve both challenges: a more efficient utilization of the grid and coping with the rising complexity of the system. There is currently no simulation in existence which helps the operators of the grid to make the correct decisions while optimizing the load balancing strategy. This paper presents a proof of concept in which the computing jobs at the Tier 1 center GridKa are modeled and simulated. To model the computing jobs we extended the Palladio simulator with a mechanism to simulate load balancing strategies. Furthermore, we implemented an automated model parameter analysis and model creation.
Finally, the simulation results are validated using real-word performance data. Our results suggest that simulating larger parts of the grid is feasible and can help to optimize the utilization of the grid.
© 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.
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.