| Hauptseite > Publikationsdatenbank > Enabling dynamic and intelligent workflows for HPC, data analytics, and AI convergence > print |
| 001 | 907436 | ||
| 005 | 20230123110616.0 | ||
| 024 | 7 | _ | |a 10.1016/j.future.2022.04.014 |2 doi |
| 024 | 7 | _ | |a 0167-739X |2 ISSN |
| 024 | 7 | _ | |a 1872-7115 |2 ISSN |
| 024 | 7 | _ | |a 2128/31145 |2 Handle |
| 024 | 7 | _ | |a altmetric:127394423 |2 altmetric |
| 024 | 7 | _ | |a WOS:000808123100004 |2 WOS |
| 037 | _ | _ | |a FZJ-2022-02034 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 004 |
| 100 | 1 | _ | |a Ejarque, Jorge |0 0000-0003-4725-5097 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Enabling dynamic and intelligent workflows for HPC, data analytics, and AI convergence |
| 260 | _ | _ | |a Amsterdam [u.a.] |c 2022 |b Elsevier Science |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1652180156_28215 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a The evolution of High-Performance Computing (HPC) platforms enables the design and execution of progressively larger and more complex workflow applications in these systems. The complexity comes not only from the number of elements that compose the workflows but also from the type of computations they perform. While traditional HPC workflows target simulations and modelling of physical phenomena, current needs require in addition data analytics (DA) and artificial intelligence (AI) tasks. However, the development of these workflows is hampered by the lack of proper programming models and environments that support the integration of HPC, DA, and AI, as well as the lack of tools to easily deploy and execute the workflows in HPC systems. To progress in this direction, this paper presents use cases where complex workflows are required and investigates the main issues to be addressed for the HPC/DA/AI convergence. Based on this study, the paper identifies the challenges of a new workflow platform to manage complex workflows. Finally, it proposes a development approach for such a workflow platform addressing these challenges in two directions: first, by defining a software stack that provides the functionalities to manage these complex workflows; and second, by proposing the HPC Workflow as a Service (HPCWaaS) paradigm, which leverages the software stack to facilitate the reusability of complex workflows in federated HPC infrastructures. Proposals presented in this work are subject to study and development as part of the EuroHPC eFlows4HPC project. |
| 536 | _ | _ | |a 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511) |0 G:(DE-HGF)POF4-5112 |c POF4-511 |f POF IV |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de |
| 700 | 1 | _ | |a Badia, Rosa M. |0 0000-0003-2941-5499 |b 1 |
| 700 | 1 | _ | |a Albertin, Loïc |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Aloisio, Giovanni |0 0000-0001-5902-6983 |b 3 |
| 700 | 1 | _ | |a Baglione, Enrico |0 P:(DE-HGF)0 |b 4 |
| 700 | 1 | _ | |a Becerra, Yolanda |0 0000-0003-2357-7796 |b 5 |
| 700 | 1 | _ | |a Boschert, Stefan |0 0000-0002-3719-5345 |b 6 |
| 700 | 1 | _ | |a Berlin, Julian R. |0 P:(DE-HGF)0 |b 7 |
| 700 | 1 | _ | |a D’Anca, Alessandro |0 0000-0002-0372-2530 |b 8 |
| 700 | 1 | _ | |a Elia, Donatello |0 0000-0002-9206-2385 |b 9 |
| 700 | 1 | _ | |a Exertier, François |0 P:(DE-HGF)0 |b 10 |
| 700 | 1 | _ | |a Fiore, Sandro |0 P:(DE-HGF)0 |b 11 |
| 700 | 1 | _ | |a Flich, José |0 P:(DE-HGF)0 |b 12 |
| 700 | 1 | _ | |a Folch, Arnau |0 0000-0002-0677-6366 |b 13 |
| 700 | 1 | _ | |a Gibbons, Steven J. |0 0000-0002-7822-0244 |b 14 |
| 700 | 1 | _ | |a Koldunov, Nikolay |0 0000-0002-3365-8146 |b 15 |
| 700 | 1 | _ | |a Lordan, Francesc |0 0000-0002-9845-8890 |b 16 |
| 700 | 1 | _ | |a Lorito, Stefano |0 0000-0002-1458-2131 |b 17 |
| 700 | 1 | _ | |a Løvholt, Finn |0 0000-0003-1019-7321 |b 18 |
| 700 | 1 | _ | |a Macías, Jorge |0 0000-0002-3010-8050 |b 19 |
| 700 | 1 | _ | |a Marozzo, Fabrizio |0 0000-0001-7887-1314 |b 20 |
| 700 | 1 | _ | |a Michelini, Alberto |0 P:(DE-HGF)0 |b 21 |
| 700 | 1 | _ | |a Monterrubio-Velasco, Marisol |0 0000-0003-0790-1832 |b 22 |
| 700 | 1 | _ | |a Pienkowska, Marta |0 0000-0002-8207-1464 |b 23 |
| 700 | 1 | _ | |a de la Puente, Josep |0 0000-0003-2608-1526 |b 24 |
| 700 | 1 | _ | |a Queralt, Anna |0 0000-0003-2782-2955 |b 25 |
| 700 | 1 | _ | |a Quintana-Ortí, Enrique S. |0 P:(DE-HGF)0 |b 26 |
| 700 | 1 | _ | |a Rodríguez, Juan E. |0 0000-0002-4715-2154 |b 27 |
| 700 | 1 | _ | |a Romano, Fabrizio |0 0000-0003-2725-3596 |b 28 |
| 700 | 1 | _ | |a Rossi, Riccardo |0 0000-0003-0528-7074 |b 29 |
| 700 | 1 | _ | |a Rybicki, Jedrzej |0 P:(DE-Juel1)144343 |b 30 |
| 700 | 1 | _ | |a Kupczyk, Miroslaw |0 P:(DE-HGF)0 |b 31 |
| 700 | 1 | _ | |a Selva, Jacopo |0 0000-0001-6263-6934 |b 32 |
| 700 | 1 | _ | |a Talia, Domenico |0 P:(DE-HGF)0 |b 33 |
| 700 | 1 | _ | |a Tonini, Roberto |0 0000-0001-7617-7206 |b 34 |
| 700 | 1 | _ | |a Trunfio, Paolo |0 P:(DE-HGF)0 |b 35 |
| 700 | 1 | _ | |a Volpe, Manuela |0 0000-0003-4551-3339 |b 36 |
| 773 | _ | _ | |a 10.1016/j.future.2022.04.014 |g p. S0167739X22001364 |0 PERI:(DE-600)2020551-X |p 414-429 |t Future generation computer systems |v 134 |y 2022 |x 0167-739X |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/907436/files/eFlows4HPC.pdf |y Published on 2022-04-27. Available in OpenAccess from 2024-04-27. |
| 909 | C | O | |o oai:juser.fz-juelich.de:907436 |p openaire |p open_access |p VDB |p driver |p dnbdelivery |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 30 |6 P:(DE-Juel1)144343 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action |1 G:(DE-HGF)POF4-510 |0 G:(DE-HGF)POF4-511 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Enabling Computational- & Data-Intensive Science and Engineering |9 G:(DE-HGF)POF4-5112 |x 0 |
| 914 | 1 | _ | |y 2022 |
| 915 | _ | _ | |a Creative Commons Attribution-NonCommercial-NoDerivs CC BY-NC-ND 4.0 |0 LIC:(DE-HGF)CCBYNCND4 |2 HGFVOC |
| 915 | _ | _ | |a Embargoed OpenAccess |0 StatID:(DE-HGF)0530 |2 StatID |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2021-02-04 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2021-02-04 |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b FUTURE GENER COMP SY : 2021 |d 2022-11-09 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2022-11-09 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2022-11-09 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2022-11-09 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1160 |2 StatID |b Current Contents - Engineering, Computing and Technology |d 2022-11-09 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2022-11-09 |
| 915 | _ | _ | |a IF >= 5 |0 StatID:(DE-HGF)9905 |2 StatID |b FUTURE GENER COMP SY : 2021 |d 2022-11-09 |
| 920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
| 980 | 1 | _ | |a FullTexts |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|