CORDIS · 957407 · H2020
DAPHNE Integrated Data Analysis Pipelines for Large-Scale Data Management, HPC, and Machine Learning
Coordinator: KNOW CENTER RESEARCH GMBH (AT)
Modern data-driven applications leverage large, heterogeneous data collections to find interesting patterns, and build robust machine learning (ML) models for accurate predictions. Large data sizes and advanced analytics spurred the development and adoption of data-parallel computation frameworks like Apache Spark or Flink as well as distributed ML systems like MLlib, TensorFlow, or PyTorch. A key observation is that these new systems share many techniques with traditional high-performance computing (HPC), and the architecture of underlying HW clusters converges. Yet, the programming paradigm…
About Horizon 2020 (2014–2020)
Horizon 2020 was the EU's flagship research and innovation programme for 2014–2020, with a budget of around €77 billion. It bundled FP7's strands with the EIT and the Competitiveness and Innovation Programme, introduced a stronger societal-challenge orientation, and pushed the funding logic toward closer-to-market innovation. New calls closed in 2020 but funded projects continued through 2024.
EU contribution: €6.6M awarded to the consortium. The project runs over approximately 4 years from 2020-12-01 to 2024-11-30.
Full record on CORDIS — partners, deliverables, publications, news.
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Frequently asked questions
- Who funds this research project?
- This project is funded by the European Union through the Horizon 2020 (2014–2020) programme, under the RIA funding scheme.
- What is the EU contribution?
- The European Commission contributes €6.6M toward a total project budget of €6.6M.
- Which EU programme funds it?
- The project is funded under Horizon 2020 (2014–2020), call H2020-ICT-2018-20.
- Who coordinates the project?
- The project is coordinated by KNOW CENTER RESEARCH GMBH (AT).
- What is the project timeline?
- The project runs from 2020-12-01 to 2024-11-30 — approximately 4 years.
- Where can I find the full project record?
- The complete record — partners, deliverables, publications and news — is published on CORDIS under project ID 957407.