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DAPHNE Runtime: Harnessing Parallelism for Integrated Data Analysis Pipelines

  • Conference paper
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Euro-Par 2023: Parallel Processing Workshops (Euro-Par 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14352))

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Abstract

Integrated data analysis pipelines combine rigorous data management and processing, high-performance computing and machine learning tasks. While these systems and operations share many compilation and runtime techniques, data analysts and scientists are currently dealing with multiple systems for each stage of their pipeline. DAPHNE is an open and extensible system infrastructure for such pipelines, including language abstractions, compilation and runtime techniques, multi-level scheduling, hardware accelerators and computational storage. In this demonstration, we focus on the DAPHNE runtime that provides the implementation of kernels for local, distributed and accelerator-enhanced operations, vectorized execution, integration with existing frameworks and libraries for productivity and interoperability, as well as efficient I/O and communication primitives.

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Notes

  1. 1.

    https://daphne-eu.eu/.

  2. 2.

    https://github.com/daphne-eu/daphne.

  3. 3.

    https://www.izum.si/en/vega-en/.

References

  1. Damme, P., et al.: DAPHNE: an open and extensible system infrastructure for integrated data analysis pipelines. In: CIDR (2022)

    Google Scholar 

  2. Lattner, C., et al.: MLIR: scaling compiler infrastructure for domain specific computation. In: CGO 2021 (2021)

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  3. D4.2: DSL Runtime Prototype. Public EU Project Deliverable (2022). https://daphne-eu.eu/wp-content/uploads/2022/12/D4.2-DSL-Runtime-Prototype.pdf

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Acknowledgements

The DAPHNE project is funded by the European Union’s Horizon 2020 research and innovation program under grant agreement number 957407 from 12/2020 through 11/2024.

Author information

Authors and Affiliations

  1. ICCS–National Technical University of Athens, Athens, Greece

    Aristotelis Vontzalidis, Stratos Psomadakis, Constantinos Bitsakos & Dimitrios Tsoumakos

  2. Know-Center GmbH/TU Graz, Graz, Austria

    Mark Dokter

  3. Graz University of Technology, Graz, Austria

    Kevin Innerebner

  4. Technische Universität Berlin, Berlin, Germany

    Patrick Damme & Matthias Boehm

  5. University of Basel, Basel, Switzerland

    Florina Ciorba & Ahmed Eleliemy

  6. University of Athens, Athens, Greece

    Vasileios Karakostas

  7. University of Maribor, Maribor, Slovenia

    Aleš Zamuda

Authors
  1. Aristotelis Vontzalidis
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  2. Stratos Psomadakis
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  3. Constantinos Bitsakos
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  4. Mark Dokter
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  5. Kevin Innerebner
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  6. Patrick Damme
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  7. Matthias Boehm
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  8. Florina Ciorba
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  9. Ahmed Eleliemy
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  10. Vasileios Karakostas
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  11. Aleš Zamuda
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  12. Dimitrios Tsoumakos
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Corresponding author

Correspondence to Dimitrios Tsoumakos .

Editor information

Editors and Affiliations

  1. University of Cyprus, Nicosia, Cyprus

    Demetris Zeinalipour

  2. University of Santiago de Compostela, Santiago de Compostela, Spain

    Dora Blanco Heras

  3. University of Cyprus, Nicosia, Cyprus

    George Pallis

  4. Cyprus University of Technology, Limassol, Cyprus

    Herodotos Herodotou

  5. University of Nicosia, Nicosia, Cyprus

    Demetris Trihinas

  6. Inria, Nantes, France

    Daniel Balouek

  7. Louisiana State University, Baton Rouge, LA, USA

    Patrick Diehl

  8. Karlsruhe Institute of Technology, Karlsruhe, Germany

    Terry Cojean

  9. Ludwig-Maximilians-Universität, Munich, Germany

    Karl Fürlinger

  10. Roskilde University, Roskilde, Denmark

    Maja Hanne Kirkeby

  11. Bank of Italy, Rome, Italy

    Matteo Nardelli

  12. Roma Tre University, Rome, Italy

    Pierangelo Di Sanzo

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© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Vontzalidis, A. et al. (2024). DAPHNE Runtime: Harnessing Parallelism for Integrated Data Analysis Pipelines. In: Zeinalipour, D., et al. Euro-Par 2023: Parallel Processing Workshops. Euro-Par 2023. Lecture Notes in Computer Science, vol 14352. Springer, Cham. https://doi.org/10.1007/978-3-031-48803-0_25

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  • DOI: https://doi.org/10.1007/978-3-031-48803-0_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-48802-3

  • Online ISBN: 978-3-031-48803-0

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