Progress in Machine Learning Studies for the CMS Computing Infrastructure

Bonacorsi, Daniele; Kuznetsov, Valentin; Magini, Nicolo; Diotalevi, Tommaso; Repeccka, Aurimas; Matonis, Zygimantas; Kancis, Kipras

doi:10.22323/1.293.0023

Title: Progress in Machine Learning Studies for the CMS Computing Infrastructure

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Abstract

Here, computing systems for LHC experiments developed together with Grids worldwide. While a complete description of the original Grid-based infrastructure and services for LHC experiments and its recent evolutions can be found elsewhere, it is worth to mention here the scale of the computing resources needed to fulfill the needs of LHC experiments in Run-1 and Run-2 so far.

Authors:

Bonacorsi, Daniele ^[1]; Kuznetsov, Valentin ^[2]; Magini, Nicolo ^[3]; Diotalevi, Tommaso ^[1]; Repeccka, Aurimas ^[4]; Matonis, Zygimantas ^[4]; Kancis, Kipras ^[4]

Univ. of Bologna (Italy)
Cornell Univ., Ithaca, NY (United States)
Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
Vilnius Univ. (Lithuania)

Publication Date:: Wed Dec 06 00:00:00 EST 2017

Research Org.:: Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)

Sponsoring Org.:: USDOE Office of Science (SC), High Energy Physics (HEP)

OSTI Identifier:: 1420911

Report Number(s):: FERMILAB-CONF-17-649
Journal ID: ISSN 1824-8039; 1642348

Grant/Contract Number:: AC02-07CH11359

Resource Type:: Accepted Manuscript

Journal Name:: PoS Proceedings of Science

Additional Journal Information:: Journal Volume: 293; Journal ID: ISSN 1824-8039

Publisher:: SISSA

Country of Publication:: United States

Language:: English

Subject:: 97 MATHEMATICS AND COMPUTING

Citation Formats


                    Bonacorsi, Daniele, Kuznetsov, Valentin, Magini, Nicolo, Diotalevi, Tommaso, Repeccka, Aurimas, Matonis, Zygimantas, and Kancis, Kipras. Progress in Machine Learning Studies for the CMS Computing Infrastructure.  United States: N. p., 2017. 
Web.  doi:10.22323/1.293.0023.

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                    Bonacorsi, Daniele, Kuznetsov, Valentin, Magini, Nicolo, Diotalevi, Tommaso, Repeccka, Aurimas, Matonis, Zygimantas, & Kancis, Kipras. Progress in Machine Learning Studies for the CMS Computing Infrastructure.  United States.  https://doi.org/10.22323/1.293.0023

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                    Bonacorsi, Daniele, Kuznetsov, Valentin, Magini, Nicolo, Diotalevi, Tommaso, Repeccka, Aurimas, Matonis, Zygimantas, and Kancis, Kipras. Wed .  
"Progress in Machine Learning Studies for the CMS Computing Infrastructure".  United States.  https://doi.org/10.22323/1.293.0023.  https://www.osti.gov/servlets/purl/1420911.

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@article{osti_1420911,

  title        = {Progress in Machine Learning Studies for the CMS Computing Infrastructure},

  author       = {Bonacorsi, Daniele and Kuznetsov, Valentin and Magini, Nicolo and Diotalevi, Tommaso and Repeccka, Aurimas and Matonis, Zygimantas and Kancis, Kipras},

  abstractNote = {Here, computing systems for LHC experiments developed together with Grids worldwide. While a complete description of the original Grid-based infrastructure and services for LHC experiments and its recent evolutions can be found elsewhere, it is worth to mention here the scale of the computing resources needed to fulfill the needs of LHC experiments in Run-1 and Run-2 so far.},

  doi          = {10.22323/1.293.0023},

  journal      = {PoS Proceedings of Science},

  number       = ,

  volume       = 293,

  place        = {United States},

  year         = {Wed Dec 06 00:00:00 EST 2017},

  month        = {Wed Dec 06 00:00:00 EST 2017}

}

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