DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines

Patrick Damme, Marius Birkenbach, Constantinos Bitsakos, Matthias Boehm, Philippe Bonnet, Florina Ciorba, Mark Dokter, Pawel Dowgiallo, Ahmed Eleliemy, Christian Faerber, Georgios Goumas, Dirk Habich, Niclas Hedam, Marlies Hofer, Wenjun Huang, Kevin Innerebner, Vasileios Karakostas, Roman Kern, Tomaž Kosar, Alexander KrauseDaniel 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, Pınar Tözün, Wojciech Ulatowski, Yuanyuan Wang, Izajasz Wrosz, Aleš Zamuda, Ce Zhang, Xiao Xiang Zhu

Research output: Contribution to conferencePaperpeer-review

15 Scopus citations

Abstract

Integrated data analysis (IDA) pipelines-that combine data management (DM) and query processing, high-performance computing (HPC), and machine learning (ML) training and scoring-become increasingly common in practice. Interestingly, systems of these areas share many compilation and runtime techniques, and the used-increasingly heterogeneous-hardware infrastructure converges as well. Yet, the programming paradigms, cluster resource management, data formats and representations, as well as execution strategies differ substantially. DAPHNE is an open and extensible system infrastructure for such IDA pipelines, including language abstractions, compilation and runtime techniques, multi-level scheduling, hardware (HW) accelerators, and computational storage for increasing productivity and eliminating unnecessary overheads. In this paper, we make a case for IDA pipelines, describe the overall DAPHNE system architecture, its key components, and the design of a vectorized execution engine for computational storage, HW accelerators, as well as local and distributed operations. Preliminary experiments that compare DAPHNE with MonetDB, Pandas, DuckDB, and TensorFlow show promising results.

Original languageEnglish
StatePublished - 2022
Event12th Annual Conference on Innovative Data Systems Research, CIDR 2022 - Santa Cruz, United States
Duration: 9 Jan 202212 Jan 2022

Conference

Conference12th Annual Conference on Innovative Data Systems Research, CIDR 2022
Country/TerritoryUnited States
CitySanta Cruz
Period9/01/2212/01/22

Fingerprint

Dive into the research topics of 'DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines'. Together they form a unique fingerprint.

Cite this