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dc.contributor.authorBadia Sala, Rosa Maria
dc.contributor.authorEjarque Artigas, Jorge
dc.contributor.authorLordan Gomis, Francesc
dc.contributor.authorLezzi, Daniele
dc.contributor.authorConejero Bañón, Javier
dc.contributor.authorÁlvarez Cid-Fuentes, Javier
dc.contributor.authorBecerra Fontal, Yolanda
dc.contributor.authorQueralt Calafat, Anna
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2020-06-12T13:04:16Z
dc.date.available2020-06-12T13:04:16Z
dc.date.issued2019
dc.identifier.citationBadia, R.M. [et al.]. Workflow environments for advanced cyberinfrastructure platforms. A: IEEE International Conference on Distributed Computing Systems. "2019 39th IEEE International Conference on Distributed Computing Systems, ICDCS 2019: Richardson, Texas, United States, 7-9 July 2019: proceedings". Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 1720-1729.
dc.identifier.isbn978-1-7281-2519-0
dc.identifier.otherhttp://arxiv.org/abs/2006.07066
dc.identifier.urihttp://hdl.handle.net/2117/190641
dc.description.abstractProgress in science is deeply bound to the effective use of high-performance computing infrastructures and to the efficient extraction of knowledge from vast amounts of data. Such data comes from different sources that follow a cycle composed of pre-processing steps for data curation and preparation for subsequent computing steps, and later analysis and analytics steps applied to the results. However, scientific workflows are currently fragmented in multiple components, with different processes for computing and data management, and with gaps in the viewpoints of the user profiles involved. Our vision is that future workflow environments and tools for the development of scientific workflows should follow a holistic approach, where both data and computing are integrated in a single flow built on simple, high-level interfaces. The topics of research that we propose involve novel ways to express the workflows that integrate the different data and compute processes, dynamic runtimes to support the execution of the workflows in complex and heterogeneous computing infrastructures in an efficient way, both in terms of performance and energy. These infrastructures include highly distributed resources, from sensors and instruments, and devices in the edge, to High-Performance Computing and Cloud computing resources. This paper presents our vision to develop these workflow environments and also the steps we are currently following to achieve it.
dc.description.sponsorshipThis work has been supported by the Spanish Government (SEV2015-0493), by the Spanish Ministry of Science and Innovation (contract TIN2015-65316-P), by Generalitat de Catalunya (contract 2014-SGR-1051). Javier Conejero postdoctoral contract is co-financed by the Ministry of Economy and Competitiveness under Juan de la Cierva Formacion´ postdoctoral fellowship number FJCI-2015-24651. This work is supported by the H2020 mF2C project (730929) and the CLASS project (780622). The participation of Rosa M Badia in the BDEC2 meetings is supported by the EXDCI project (800957). The dislib library developments are partially funded under the project agreement between BSC and FUJITSU.
dc.format.extent10 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Informàtica::Arquitectura de computadors::Arquitectures distribuïdes
dc.subject.lcshCloud computing
dc.subject.lcshHigh performance computing
dc.subject.lcshBig data
dc.subject.otherScientific workflows
dc.subject.otherComputing continuum platforms
dc.subject.otherBig data and high-performance computing convergence
dc.subject.otherIntelligent runtimes
dc.titleWorkflow environments for advanced cyberinfrastructure platforms
dc.typeConference report
dc.subject.lemacComputació en núvol
dc.subject.lemacMacrodades
dc.contributor.groupUniversitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
dc.identifier.doi10.1109/ICDCS.2019.00171
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://ieeexplore.ieee.org/abstract/document/8885062
dc.rights.accessOpen Access
local.identifier.drac28657388
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/730929/EU/Towards an Open, Secure, Decentralized and Coordinated Fog-to-Cloud Management Ecosystem/mF2C
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/1PE/TIN2015-65316-P
dc.relation.projectidinfo:eu-repo/grantAgreement/AGAUR/V PRI/2014 SGR 1051
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/780622/EU/Edge and CLoud Computation: A Highly Distributed Software Architecture for Big Data AnalyticS/CLASS
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/1PE/SEV2015-0493
local.citation.authorBadia, R.M.; Ejarque, J.; Lordan, F.; Lezzi, D.; Conejero, J.; Álvarez, J.; Becerra, Y.; Queralt, A.
local.citation.contributorIEEE International Conference on Distributed Computing Systems
local.citation.publicationName2019 39th IEEE International Conference on Distributed Computing Systems, ICDCS 2019: Richardson, Texas, United States, 7-9 July 2019: proceedings
local.citation.startingPage1720
local.citation.endingPage1729


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