CERN Accelerating science

CERN Published Articles

Последние добавления:
2017-12-11
10:48
Neodymium-140 DOTA-LM3: Evaluation of an In Vivo Generator for PET with a Non-Internalizing Vector / IS528 Collaboration
- Published in : 10.3389/fmed.2017.00098

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2017-12-09
06:49
Windows Terminal Servers Orchestration / Bukowiec, Sebastian (CERN) ; Gaspar, Ricardo (New Lisbon U.) ; Smith, Tim (CERN)
Windows Terminal Servers provide application gateways for various parts of the CERN accelerator complex, used by hundreds of CERN users every day. The combination of new tools such as Puppet, HAProxy and Microsoft System Center suite enable automation of provisioning workflows to provide a terminal server infrastructure that can scale up and down in an automated manner. [...]
2017 - 8 p. - Published in : J. Phys. : Conf. Ser. 898 (2017) 082025 Fulltext: PDF;
In : 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016, San Francisco, Usa, 10 - 14 Oct 2016, pp.082025

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2017-12-09
06:49
CERN openlab: Engaging industry for innovation in the LHC Run 3-4 R&D; programme / Girone, M (CERN) ; Purcell, A (CERN) ; Di Meglio, A (CERN) ; Rademakers, F (CERN) ; Gunne, K (CERN) ; Pachou, M (CERN) ; Pavlou, S (CERN)
LHC Run3 and Run4 represent an unprecedented challenge for HEP computing in terms of both data volume and complexity. New approaches are needed for how data is collected and filtered, processed, moved, stored and analysed if these challenges are to be met with a realistic budget. [...]
2017 - 8 p. - Published in : J. Phys. : Conf. Ser. 898 (2017) 072049 Fulltext: PDF;
In : 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016, San Francisco, Usa, 10 - 14 Oct 2016, pp.072049

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2017-12-09
06:49
Machine learning developments in ROOT / Bagoly, A (Eotvos U.) ; Bevan, A (Queen Mary, U. of London) ; Carnes, A (Florida U.) ; Gleyzer, S V (Florida U.) ; Moneta, L (CERN) ; Moudgil, A (Hyderabad, IIIT) ; Pfreundschuh, S (Chalmers U. Tech.) ; Stevenson, T (Queen Mary, U. of London) ; Wunsch, S (KIT, Karlsruhe) ; Zapata, O (Antioquia U.)
ROOT is a software framework for large-scale data analysis that provides basic and advanced statistical methods used by high-energy physics experiments. It includes machine learning tools from the ROOT-integrated Toolkit for Multivariate Analysis (TMVA). [...]
2017 - 8 p. - Published in : J. Phys. : Conf. Ser. 898 (2017) 072046 Fulltext: PDF;
In : 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016, San Francisco, Usa, 10 - 14 Oct 2016, pp.072046

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2017-12-09
06:49
PODIO: An Event-Data-Model Toolkit for High Energy Physics Experiments / Gaede, F (DESY) ; Hegner, B (CERN) ; Mato, P (CERN)
PODIO is a C++ library that supports the automatic creation of event data models (EDMs) and efficient I/O code for HEP experiments. It is developed as a new EDM Toolkit for future particle physics experiments in the context of the AIDA2020 EU programme. [...]
2017 - 6 p. - Published in : J. Phys. : Conf. Ser. 898 (2017) 072039 Fulltext: PDF;
In : 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016, San Francisco, Usa, 10 - 14 Oct 2016, pp.072039

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2017-12-09
06:49
Developing and optimizing applications in Hadoop / Kothuri, P (CERN) ; Garcia, D (CERN) ; Hermans, J (CERN)
This contribution is about sharing our recent experiences of building Hadoop based application. Hadoop ecosystem now offers myriad of tools which can overwhelm new users, yet there are successful ways these tools can be leveraged to solve problems. [...]
2017 - 8 p. - Published in : J. Phys. : Conf. Ser. 898 (2017) 072038 Fulltext: PDF;
In : 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016, San Francisco, Usa, 10 - 14 Oct 2016, pp.072038

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2017-12-09
06:49
Microservices for systematic profiling and monitoring of the refactoring process at the LHCb experiment / Mazurov, Alexander (Birmingham U.) ; Couturier, Ben (CERN) ; Popov, Dmitry (Heidelberg, Max Planck Inst.) ; Farley, Nathanael (Birmingham U.)
Any time you modify an implementation within a program, change compiler version or operating system, you should also do regression testing. You can do regression testing by rerunning existing tests against the changes to determine whether this breaks anything that worked prior to the change and by writing new tests where necessary. [...]
2017 - 8 p. - Published in : J. Phys. : Conf. Ser. 898 (2017) 072037 Fulltext: PDF;
In : 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016, San Francisco, Usa, 10 - 14 Oct 2016, pp.072037

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2017-12-09
06:49
First results from a combined analysis of CERN computing infrastructure metrics / Duellmann, Dirk (CERN) ; Nieke, Christian (Braunschweig Tech. U.)
The IT Analysis Working Group (AWG) has been formed at CERN across individual computing units and the experiments to attempt a cross cutting analysis of computing infrastructure and application metrics. In this presentation we will describe the first results obtained using medium/long term data (1 months — 1 year) correlating box level metrics, job level metrics from LSF and HTCondor, IO metrics from the physics analysis disk pools (EOS) and networking and application level metrics from the experiment dashboards. [...]
2017 - 8 p. - Published in : J. Phys. : Conf. Ser. 898 (2017) 072035 Fulltext: PDF;
In : 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016, San Francisco, Usa, 10 - 14 Oct 2016, pp.072035

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2017-12-09
06:49
Hadoop and friends - first experience at CERN with a new platform for high throughput analysis steps / Duellmann, Dirk (CERN) ; Surdy, Kacper (CERN) ; Menichetti, Luca (CERN) ; Toebbicke, Rainer (CERN)
The statistical analysis of infrastructure metrics comes with several specific challenges, including the fairly large volume of unstructured metrics from a large set of independent data sources. Hadoop and Spark provide an ideal environment in particular for the first steps of skimming rapidly through hundreds of TB of low relevance data to find and extract the much smaller data volume that is relevant for statistical analysis and modelling. [...]
2017 - 8 p. - Published in : J. Phys. : Conf. Ser. 898 (2017) 072034 Fulltext: PDF;
In : 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016, San Francisco, Usa, 10 - 14 Oct 2016, pp.072034

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2017-12-09
06:49
A browser-based event display for the CMS Experiment at the LHC using WebGL / McCauley, T (Notre Dame U.)
Modern web browsers are powerful and sophisticated applications that support an ever-wider range of uses. One such use is rendering high-quality, GPU-accelerated, interactive 2D and 3D graphics in an HTML canvas. [...]
2017 - 8 p. - Published in : J. Phys. : Conf. Ser. 898 (2017) 072030 Fulltext: PDF;
In : 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016, San Francisco, Usa, 10 - 14 Oct 2016, pp.072030

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