Rezultaty
Initial description of the Exascale monitoring architecture.
Extreme scale monitoring architecture - FinalFinal description of the Exascale monitoring architecture
Strategies and methodology for data movement in ExascaleReport that presents an the load balance and optimization techniques designed for data movement in Exascale sytems
Dissemination and training report - Second yearReport that describes the workpackages activities results in the second year
Data collection and mining for Exascale systemsDescription of the explored data collection and mining methodologies.
Final ReportReport that presents an overview of the activities that were fulfilled during the project duration
RequirementsThis deliverable will consists of two-parts; the first in the shape of requirements analysis strategy and the second stage in the shape of the requirement repository.
Paradigms and models at run-time - final reportReport that presents the evaluation of the advance of the stateoftheart by using the WP2 concepts and tools for Exascale systems
Applications designThis report comprises detailed descriptions of the applications, the list of used WP2-WP4 concepts, their modes of integration with the applications, recommendations and APIs that will be taken into account in the redesign process, as well as the key performance indicators for the future evaluation of the improvements in performance through the re-design and re-implementation.
Validation of project outcomes through applicationsFinal validation and evaluation of the newly developed tools by WP2WP4 using the proposed use cases
Programming paradigms supporting extreme dataInclude the concepts and proposals from T2.1 and T2.2.
Auto-tune of Exascale applicationsFinal report providing detailed description of the developed tools related to the Exascale applications auto tuning
Strategies and methodology for Exascale data managementDescription of the predictive and adaptive data layout strategies designed for Exascale.
Dissemination and training report - First yearReport that describes the work packages activities results in the first half of the project.
Techniques for in-memory real-time data analytics support at Exascale levelReport that presents an the load balance and optimization techniques designed for data movement in Exascale sytems
Adaptive analysis of application behaviourReport that presents an overview of the novel methodologies and tools for adaptive analysis of applica tions behavior
Communication, collaboration, exploitation and standardization report - Third yearReport that describes the results of the activities in the project related to exploitation and standardization
Monitoring data collection and mining for Exascale systemsDescription of the explored data collection and mining methodologies.
Public Web site.
Description of the explored data collection and mining methodologies.
Libraries and tools to support extreme data processingCollection of software prototypes with internal user manuals as results of T2.1-T2.4.
Applications - alpha versionThe first versions of the applications using the software prototypes strategies methodologies and concepts from WP2 WP4 and the feedback for their improvement internal user manuals
Run-time support for programming extreme data applicationRuntime system prototype with detailed user manual
Framework for programming extreme data applicationCollection of software prototypes with detailed user manuals as results of T21T23
Low-overhead software instrumentation and monitoringDescription of the explored instrumentation and monitoring methodologies and tools.
Report that presents the evaluation of the advance of the stateoftheart by using the WP2 concepts and tools for Exascale systems
Publikacje
Autorzy:
Riccardo Cantini, Fabrizio Marozzo, Alessio Orsino, Domenico Talia, Paolo Trunfio
Opublikowane w:
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MDPI
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Brain Sciences, Numer 11/2, 2021, Strona(/y) 168, ISSN 2076-3425
Wydawca:
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IEEE Access, Numer 9, 2021, Strona(/y) 47354-47364, ISSN 2169-3536
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The Journal of Supercomputing, 2019, ISSN 0920-8542
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Javier López-Gómez, Javier Fernández Muñoz, David del Rio Astorga, Manuel F. Dolz, J. Daniel Garcia
Opublikowane w:
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Elsevier BV
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Opublikowane w:
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Opublikowane w:
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MDPI
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Opublikowane w:
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Opublikowane w:
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Wydawca:
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DOI:
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2020 IEEE 27th International Conference on High Performance Computing, Data, and Analytics (HiPC), 2020, Strona(/y) 243-250, ISBN 978-1-6654-2292-5
Wydawca:
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Opublikowane w:
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Opublikowane w:
EuroPAR 2019, Numer 1, 2019
Wydawca:
Springer
Autorzy:
Javier Garcia-Blas, David del Rio Astorga, J. Daniel Garcia, Jesus Carretero
Opublikowane w:
2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), 2019, Strona(/y) 631-637, ISBN 978-1-7281-0912-1
Wydawca:
IEEE
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2019 IEEE International Conference on Advanced Scientific Computing (ICASC), 2019, Strona(/y) 1-5, ISBN 978-1-7281-4454-2
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