Abstract
High Energy Physics (HEP) data analysis consists of simulating and analysing events in particle physics. In order to understand physics phenomena, one must collect and go through a very large quantity of data generated by particle accelerators and software simulations. This data analysis can be done using the cloud computing paradigm in distributed computing environment where data and computation can be located in different, geographically distant, data centres. This adds complexity and overhead to networking. In this paper, we study how the networking solution and its performance affects the efficiency and energy consumption of HEP computing. Our results indicate that higher latency both prolongs the processing time and increases the energy consumption.
| Original language | English |
|---|---|
| Title of host publication | BMSD 2016 - Proceedings of the 6th International Symposium on Business Modeling and Software Design |
| Editors | Boris Shishkov |
| Publisher | SciTePress |
| Pages | 227-234 |
| Number of pages | 8 |
| ISBN (Electronic) | 9789897581908 |
| Publication status | Published - 1 Jan 2016 |
| MoE publication type | A4 Conference publication |
| Event | International Symposium on Business Modeling and Software Design - Rhodes, Greece Duration: 20 Jun 2016 → 22 Jun 2016 Conference number: 6 |
Conference
| Conference | International Symposium on Business Modeling and Software Design |
|---|---|
| Abbreviated title | BMSD |
| Country/Territory | Greece |
| City | Rhodes |
| Period | 20/06/2016 → 22/06/2016 |
Keywords
- Energy efficiency
- Latency
- Network
- Openstack
- Scientific computing
