CMS readiness for multi-core workload scheduling

Journal Article · Wed Nov 22 00:00:00 EST 2017 · Journal of Physics. Conference Series

DOI:https://doi.org/10.1088/1742-6596/898/5/052030· OSTI ID:1420916

Yzquierdo, A. Perez-Calero ^[1]; Balcas, J. ^[2]; Hernandez, J. ^[3]; Aftab Khan, F. ^[4]; Letts, J. ^[5]; Mason, D. ^[6]; Verguilov, V. ^[7]

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1. Pord d'Informacio Cientifica, Barcelona (Spain); Research Centre for Energy, Environment and Technology (CIEMAT), Madrid (Spain)
2. California Inst. of Technology (CalTech), Pasadena, CA (United States)
3. Research Centre for Energy, Environment and Technology (CIEMAT), Madrid (Spain)
4. Quaid-I-Azam Univ., Islamabad (Pakistan)
5. Univ. of California, San Diego, CA (United States)
6. Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
7. Bulgarian Academy of Sciences, Sofia (Bulgaria)

In the present run of the LHC, CMS data reconstruction and simulation algorithms benefit greatly from being executed as multiple threads running on several processor cores. The complexity of the Run 2 events requires parallelization of the code to reduce the memory-per- core footprint constraining serial execution programs, thus optimizing the exploitation of present multi-core processor architectures. The allocation of computing resources for multi-core tasks, however, becomes a complex problem in itself. The CMS workload submission infrastructure employs multi-slot partitionable pilots, built on HTCondor and GlideinWMS native features, to enable scheduling of single and multi-core jobs simultaneously. This provides a solution for the scheduling problem in a uniform way across grid sites running a diversity of gateways to compute resources and batch system technologies. This paper presents this strategy and the tools on which it has been implemented. The experience of managing multi-core resources at the Tier-0 and Tier-1 sites during 2015, along with the deployment phase to Tier-2 sites during early 2016 is reported. The process of performance monitoring and optimization to achieve efficient and flexible use of the resources is also described.

• Research Organization: Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
• Sponsoring Organization: USDOE Office of Science (SC), High Energy Physics (HEP)
• Grant/Contract Number: AC02-07CH11359
• OSTI ID: 1420916
• Report Number(s): FERMILAB-CONF-16-755-CD; 1638487
• Journal Information: Journal of Physics. Conference Series, Vol. 898, Issue 5; Conference: 22nd International Conference on Computing in High Energy and Nuclear Physics, San Francisco, CA, 10/10-10/14/2016; ISSN 1742-6588
• Publisher: IOP Publishing
• Country of Publication: United States
• Language: English

Related Subjects

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