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DAPHNE: Integrated Data Analysis Pipelines for Large-Scale Data Management, HPC, and Machine Learning
Third-party funded project |
Project title |
DAPHNE: Integrated Data Analysis Pipelines for Large-Scale Data Management, HPC, and Machine Learning |
Principal Investigator(s) |
Ciorba, Florina M.
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Project Members |
Eleliemy, Ahmed Hamdy Mohamed
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Organisation / Research unit |
Departement Mathematik und Informatik / High Performance Computing (Ciorba) |
Department |
Departement Mathematik und Informatik / High Performance Computing (Ciorba) |
Project Website |
https://daphne-eu.eu |
Project start |
01.10.2020 |
Probable end |
30.09.2024 |
Status |
Active |
Abstract |
The DAPHNE project aims to define and build an open and extensible system infrastructure for integrated data analysis pipelines, including data management and processing, high-performance computing (HPC), and machine learning (ML) training and scoring. Key observations are that (1) systems of these areas share many compilation and runtime techniques, (2) there is a trend towards complex data analysis pipelines that combine these systems, and (3) the used, increasingly heterogeneous, hardware infrastructure converges as well. Yet, the programming paradigms, cluster resource management, as well as data formats and representations differ substantially. Therefore, this project aims – with a joint consortium of experts from the data management, ML systems, and HPC communities – at systematically investigating the necessary system infrastructure, language abstractions, compilation and runtime techniques, as well as systems and tools necessary to increase the productivity when building such data analysis pipelines, and eliminating unnecessary performance bottlenecks. |
Keywords |
System Architecture, APIs and DSL, Hierarchical Scheduling and Task Planning, Use Cases and Benchmarking |
Financed by |
Commission of the European Union
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Published results () |
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ID |
Autor(en) |
Titel |
ISSN / ISBN |
Erschienen in |
Art der Publikation |
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4631194 |
Ihde, N.; Marten, P.; Eleliemy, A.; Poerwawinata, G.; Silva, P.; Tolovski, I.; Ciorba, F. M.; Rabl, T. |
A Survey of Big Data, HPC and Machine Learning Benchmarks |
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Publication: ConferencePaper (Artikel, die in Tagungsbänden erschienen sind) |
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4661212 |
Nina Ihde; Paula Marten; A. Eleliemy; Gabrielle Poerwawinata; P. Silva; Ilin Tolovski; Florina M. Ciorba; Tilmann Rabl |
A Survey of Big Data, High Performance Computing, and Machine Learning Benchmarks |
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Publication: ConferencePaper (Artikel, die in Tagungsbänden erschienen sind) |
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4661202 |
Patrick Damme; Marius Birkenbach; Constantinos Bitsakos; Matthias Boehm; Philippe Bonnet; Florina M. Ciorba; Mark Dokter; Pawel Dowgiallo; A. Eleliemy; Christian Faerber; Georgios I. Goumas; Dirk Habich; Niclas Hedam; Marlies Hofer; Wen-Hung Kevin Huang; Kevin Innerebner; Vasileios Karakostas; Roman Kern; Tomavz Kosar; Alexander Krause; D. Krems; Andreas Laber; Wolfgang Lehner; Eric Mier; Marcus Paradies; Bernhard Peischl; Gabrielle Poerwawinata; Stratos Psomadakis; Tilmann Rabl; Piotr Ratuszniak; Pedro Silva; Nikolai Skuppin; Andreas Starzacher; Benjamin Steinwender; Ilin Tolovski; Pinar Tözün; Wojciech Ulatowski; Yuanyuan Wang; Izajasz P. Wrosz; A. Zamuda; Ce Zhang; Xiao Xiang Zhu |
DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines |
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Publication: ConferencePaper (Artikel, die in Tagungsbänden erschienen sind) |
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4626035 |
Müller Korndörfer, Jonas H.; Eleliemy, Ahmed; Mohammed, Ali; Ciorba M., Florina |
LB4OMP: A Dynamic Load Balancing Library for Multithreaded Applications |
1045-9219 |
IEEE Transactions on parallel and distributed systems |
Publication: JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift) |
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29/03/2024
Research Database / FORSCHUNGSDATENBANK
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