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CERN Document Server 6 ჩანაწერია ნაპოვნი  ძიებას დასჭირდა 0.51 წამი. 
1.
CERN Analysis Preservation and Reuse Framework: FAIR research data services for LHC experiments / Fokianos, Pamfilos (CERN) ; Feger, Sebastian (CERN) ; Koutsakis, Ilias (CERN) ; Lavasa, Artemis (CERN) ; Maciulaitis, Rokas (CERN) ; Naim, Kamran (CERN) ; Okraska, Jan (CERN) ; Papadopoulos, Antonios (CERN) ; Rodríguez, Diego (CERN) ; Šimko, Tibor (CERN) et al.
In this paper we present the CERN Analysis Preservation service as a FAIR (Findable, Accessible, Interoperable and Reusable) research data preservation repository platform for LHC experiments. The CERN Analysis Preservation repository allows LHC collaborations to deposit and share the structured information about analyses as well as to capture the individual data assets associated to the analysis. [...]
2020 - 9 p. - Published in : EPJ Web Conf. 245 (2020) 06011 Fulltext: PDF;
In : 24th International Conference on Computing in High Energy and Nuclear Physics, Adelaide, Australia, 4 - 8 Nov 2019, pp.06011
დეტალური ჩანაწერი - მსგავსი ჩანაწერები
2.
Hybrid analysis pipelines in the REANA reproducible analysis platform / Rodríguez, Diego (CERN) ; Mačiulaitis, Rokas (CERN) ; Okraska, Jan (CERN) ; Šimko, Tibor
We introduce the feasibility of running hybrid analysis pipelines in the REANA reproducible analysis platform. The REANA platform allows researchers to specify declarative computational workflow steps describing the analysis process and to execute analysis workload on remote containerised compute clouds. [...]
2020 - 7 p. - Published in : EPJ Web Conf. 245 (2020) 06041 Fulltext: PDF;
In : 24th International Conference on Computing in High Energy and Nuclear Physics, Adelaide, Australia, 4 - 8 Nov 2019, pp.06041
დეტალური ჩანაწერი - მსგავსი ჩანაწერები
3.
Support for HTCondor high-throughput computing workflows in the REANA reusable analysis platform / Maciulaitis, Rokas (Ministere des affaires etrangeres et europeennes (FR)) ; Brener, Paul (University of Notre Dame (US)) ; Hampton, Scott (University of Notre Dame (US)) ; Hildreth, Mike (University of Notre Dame (US)) ; Hurtado Anampa, Kenyi Paolo (University of Notre Dame (US)) ; Johnson, Irena (University of Notre Dame (US)) ; Kankel, Cody (University of Notre Dame (US)) ; Okraska, Jan (University of Warsaw (PL)) ; Rodriguez Rodriguez, Diego (CERN) ; Simko, Tibor (CERN)
REANA is a reusable and reproducible data analysis platform allowing researchers to structure their analysis pipelines and run them on remote containerised compute clouds. REANA supports several different workflows systems (CWL, Serial, Yadage) and uses Kubernetes’ job execution backend. [...]
CERN-IT-2019-004.- Geneva : CERN, 2019 - 2 p. Fulltext: PDF;
In : 15th eScience IEEE International Conference, San Diego, United States, 24 - 27 Sep 2019, pp.eScience
დეტალური ჩანაწერი - მსგავსი ჩანაწერები
4. Support for HTCondor High-Throughput Computing Workflows in the REANA Reusable Analysis Platform
Reference: Poster-2019-942
Keywords:  reproducible science  computational workflows  high-throughput computing  high-performance computing  data analysis
Created: 2019. -1 p
Creator(s): Maciulaitis, Rokas; Bremer, Paul; Hampton, Scott; Hildreth, Mike; Hurtado Anampa, Kenyi Paolo [...]

REANA is a reusable and reproducible data analysis platform allowing researchers to structure their analysis pipelines and run them on remote containerised compute clouds. REANA supports several different workflows systems (CWL, Serial, Yadage) and uses Kubernetes’ job execution backend. We have designed an abstract job execution component that extends the REANA platform job execution capabilities to support multiple compute backends. We have tested the abstract job execution component with HTCondor and verified the scalability of the designed solution. The results show that the REANA platform would be able to support hybrid scientific workflows where different parts of the analysis pipelines can be executed on multiple computing backends.

Related links:
eScience 2019 Poster Session 		© CERN Geneva

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დეტალური ჩანაწერი - მსგავსი ჩანაწერები
5.
Beyond repositories: enabling actionable FAIR open data reuse services in particle physics / Rodriguez Rodriguez, Diego (CERN) ; Simko, Tibor (CERN) ; Dallmeier-Tiessen, Sunje (CERN) ; Feger, Sebastian Stefan (Universitaet Stuttgart (DE)) ; Fokianos, Pamfilos (CERN) ; Kousidis, Konstantinos ; Lavasa, Artemis (CERN) ; Maciulaitis, Rokas (Ministere des affaires etrangeres et europeennes (FR)) ; Okraska, Jan (University of Warsaw (PL)) ; Trzcinska, Anna (CERN) et al.
We describe experiences from building and operating the CERN Open Data repository platform that manages and disseminates more than one petabyte of open data from particle physics. We discuss the education and research use cases of the platform and we argue that in order to make the FAIR open data fully actionable and reusable by a variety of users, the research data repositories should evolve from focusing on resource-hosting present towards integrated service-provisioning future. [...]
IT-TALK-2019-002.- Geneva : CERN, 2019 Slides: PDF;
In : Open Repositories 2019, Hamburg, Hamburg, Germany, 10 - 14 Jun 2019
დეტალური ჩანაწერი - მსგავსი ჩანაწერები
6.
Grid site availability evaluation and monitoring at CMS / Lyons, Gaston (Fermilab) ; Maciulaitis, Rokas (Vilnius U.) ; Bagliesi, Giuseppe (INFN, Pisa ; Pisa U.) ; Lammel, Stephan (Fermilab) ; Sciabà, Andrea (CERN)
The Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) uses distributed grid computing to store, process, and analyse the vast quantity of scientific data recorded every year. The computing resources are grouped into sites and organized in a tiered structure. [...]
2017 - 8 p. - Published in : J. Phys.: Conf. Ser. 898 (2017) 092014 Fulltext: PDF;
In : 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016, San Francisco, Usa, 10 - 14 Oct 2016, pp.092014
დეტალური ჩანაწერი - მსგავსი ჩანაწერები

ასევე იხილეთ: მსგავსი ავტორის სახელები
6 Mačiulaitis, Rokas
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