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Gemünd, André
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Gemünd, André
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- PublicationOpen AccessVERCE delivers a productive e-Science environment for seismology research(2015-10-07)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;; ; ; ; ; ; ; ; ; ; ; ;; ;; ; ; ;The VERCE project has pioneered an e-Infrastructure to support researchers using established simulation codes on high-performance computers in conjunction with multiple sources of observational data. This is accessed and organised via the VERCE science gateway that makes it convenient for seismologists to use these resources from any location via the Internet. Their data handling is made flexible and scalable by two Python libraries, ObsPy and dispel4py and by data services delivered by ORFEUS and EUDAT. Provenance driven tools enable rapid exploration of results and of the relationships between data, which accelerates understanding and method improvement. These powerful facilities are integrated and draw on many other e-Infrastructures. This paper presents the motivation for building such systems, it reviews how solid-Earth scientists can make significant research progress using them and explains the architecture and mechanisms that make their construction and operation achievable. We conclude with a summary of the achievements to date and identify the crucial steps needed to extend the capabilities for seismologists, for solid-Earth scientists and for similar disciplines.100 99 - PublicationOpen AccessDARE to Perform Seismological Workflows(2019-12-09)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; The DARE e-science platform (http://project-dare.eu) offers innovative tools to ease scientific workflow development and execution exploiting efficient Cloud resources. It aims to enable on-demand numerical computations and analyses, fast large dataset handling, flexible and customisable workflow pipelines and complete provenance tracking. It also integrates available e-infrastructure services (e.g. EUDAT, EIDA) and can be linked to user developed interfaces. DARE is validated via two domain-specific pilots, one from the climate modelling community and one from the seismological research field. Focusing on the latter, the EPOS Use Case is driven by urgent issues and general user needs of solid Earth Science community, following developments and application standards in the computational seismology research society. This Use Case also benefits from the pioneering experience of previous European projects (e.g. VERCE, EPOS-IP) in this framework. We present here the development of a scientific workflow to perform a quick calculation of seismic source parameters after an earthquake. The workflow requirements include HPC calculations (on local-institutional or Cloud resources), fast data-intensive processing, provenance exploitation and seismic source inverse modelling tools. The DARE platform automatically conducts the required actions optimally mapped to computational resources, linking them together by managing intermediate data. It automatically deploys the necessary environment to perform on-demand transparent computations executing a dockerised version of the numerical simulation code on a Kubernetes cluster via a web API. Other API calls allow for remote, distributed execution of dispel4py workflows, used to describe the steps for data analysis and download of seismic recorded data via EIDA Research Infrastructure services. Well established scientific python codes, such as those for waveform misfit calculation and source inversion, are thus easily implemented in this flexible and modular structure, and executed at scale. Moreover, the pilot requirement of searching and reusing multiple simulations for the same earthquake strongly benefits from customisable management of metadata and lineage through the DARE platform exploiting the integration of S-ProvFlow with dispel4py.79 20 - PublicationOpen AccessDARE: A Reflective Platform Designed to Enable Agile Data-Driven Research on the Cloud(2019-09)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;; ; ; ;The DARE platform has been designed to help research developers deliver user-facing applications and solutions over diverse underlying e-infrastructures, data and computational contexts. The platform is Cloud-ready, and relies on the exposure of APIs, which are suitable for raising the abstraction level and hiding complexity. At its core, the platform implements the cataloguing and execution of fine-grained and Python-based dispel4py workflows as services. Reflection is achieved via a logical knowledge base, comprising multiple internal catalogues, registries and semantics, while it supports persistent and pervasive data provenance. This paper presents design and implementation aspects of the DARE platform, as well as it provides directions for future development.76 79 - PublicationRestrictedTowards Addressing CPU-Intensive Seismological Applications in Europe(Springer Berlin Heidelberg, 2013)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;Carpené, M.; CINECA, Bologna, Italy ;Klampanos, I. A.; University of Edinburgh, School of Informatics, UK ;Leong, S. H.; Leibniz Supercomputing Centre (LRZ), Garching, Germany ;Casarotti, E.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma1, Roma, Italia ;Danecek, P.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italia ;Ferini, G.; CINECA, Bologna, Italy ;Gemünd, A.; Fraunhofer Institute for Algorithms and Scientific Computing SCAI, Germany ;Krause, A.; University of Edinburgh, Edinburgh Parallel Computing Centre (EPCC), UK ;Krischer, L.; Ludwig-Maximilianis-University, Department of Earth and Environmental Sciences, Germany ;Magnoni, F.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italia ;Simon, M.; Ludwig-Maximilianis-University, Department of Earth and Environmental Sciences, Germany ;Spinuso, A.; The Royal Netherlands Meteorological Institute (KNMI), Netherlands ;Trani, L.; The Royal Netherlands Meteorological Institute (KNMI), Netherlands ;Atkinson, M.; University of Edinburgh, School of Informatics, UK ;Erbacci, G.; CINECA, Bologna, Italy ;Frank, A.; Leibniz Supercomputing Centre (LRZ), Garching, Germany ;Igel, H.; Ludwig-Maximilianis-University, Department of Earth and Environmental Sciences, Germany ;Rietbrock, H.; University of Liverpool, Department of Earth, Ocean and Ecological Sciences, UK ;Schwichtenberg, H.; Fraunhofer Institute for Algorithms and Scientific Computing SCAI, Germany ;Vilotte, J.; Institut de Physique du Globe de Paris (IPGP), France; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; Advanced application environments for seismic analysis help geosci- entists to execute complex simulations to predict the behaviour of a geophysical system and potential surface observations. At the same time data collected from seismic stations must be processed comparing recorded signals with predictions. The EU-funded project VERCE (http://verce.eu/) aims to enable specific seismological use-cases and, on the basis of requirements elicited from the seis- mology community, provide a service-oriented infrastructure to deal with such challenges. In this paper we present VERCE’s architecture, in particular relating to forward and inverse modelling of Earth models and how the, largely file-based, HPC model can be combined with data streaming operations to enhance the scala- bility of experiments. We posit that the integration of services and HPC resources in an open, collaborative environment is an essential medium for the advancement of sciences of critical importance, such as seismology.190 24