Improving efficiency of analysis jobs in CMS
| Autor: | Todor Trendafilov Ivanov, Matthias Wolf, Kenyi Hurtado Anampa, J Balcas, Diego Davila Foyo, Antonio Pérez-Calero Yzquierdo, Jose M Hernandez, Leonardo Cristella, Diego Ciangottini, Brian Bockelman, S. Belforte, James Letts, Marco Mascheroni, Anna Woodard |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Large Hadron Collider
Exploit 010308 nuclear & particles physics Physics::Instrumentation and Detectors Physics QC1-999 Distributed computing Site selection User analysis 01 natural sciences Scheduling (computing) Workflow 0103 physical sciences Detectors and Experimental Techniques 010306 general physics Worldwide LHC Computing Grid Compact Muon Solenoid |
| Zdroj: | EPJ Web of Conferences, Vol 214, p 03006 (2019) |
| Popis: | Hundreds of physicists analyze data collected by the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider using the CMS Remote Analysis Builder and the CMS global pool to exploit the resources of the Worldwide LHC Computing Grid. Efficient use of such an extensive and expensive resource is crucial. At the same time, the CMS collaboration is committed to minimizing time to insight for every scientist, by pushing for fewer possible access restrictions to the full data sample and supports the free choice of applications to run on the computing resources. Supporting such variety of workflows while preserving efficient resource usage poses special challenges. In this paper we report on three complementary approaches adopted in CMS to improve the scheduling efficiency of user analysis jobs: automatic job splitting, automated run time estimates and automated site selection for jobs. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|