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Scaling SQL to the Supercomputer for Interactive Analysis of Simulation Data

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Book cover Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation (SMC 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1512))

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Abstract

AI and simulation workloads consume and generate large amounts of data that need to be searched, transformed and merged with other data. With the goal of treating data as a first-class citizen inside a traditionally compute-centric HPC environment, we explore how the use of accelerators and high-speed interconnects can speed up tasks which otherwise constitute bottlenecks in computational discovery workflows. BlazingSQL is SQL engine that runs natively on NVIDIA GPUs and supports internode communication for fast analytics on terabyte-scale tabular data sets. We show how a fast interconnect improves query performance if leveraged through the Unified Communication X (UCX) middleware. We envision that future computing platforms will integrate accelerated database query capabilities for immediate and interactive analysis of large simulation data.

This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

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Notes

  1. 1.

    https://openucx.github.io/ucx/api/v1.10/html/group___u_c_p___w_o_r_k_e_r.html.

  2. 2.

    https://openucx.github.io/ucx/api/v1.10/html/group___u_c_p___c_o_m_m.html.

  3. 3.

    https://github.com/rapidsai/gpu-bdb.

  4. 4.

    http://tpc.org/tpcx-bb/default5.asp.

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Acknowledgments

We are grateful to Oscar Hernandez (NVIDIA) for initial conceptualization of this research. We thank Arjun Shankar (ORNL) for support. This research used resources of the Oak Ridge Leadership Computing Facility (OLCF) at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.

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Authors and Affiliations

  1. Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN, 37831, USA

    Jens Glaser, Benjamín Hernández & Matthew Baker

  2. Voltron Data, Inc., Mountain View, USA

    Felipe Aramburú, William Malpica & Rodrigo Aramburú

Authors
  1. Jens Glaser
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  2. Felipe Aramburú
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  3. William Malpica
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  4. Benjamín Hernández
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  5. Matthew Baker
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  6. Rodrigo Aramburú
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Corresponding author

Correspondence to Jens Glaser .

Editor information

Editors and Affiliations

  1. Oak Ridge National Laboratory, Oak Ridge, TN, USA

    Jeffrey Nichols

  2. Oak Ridge National Laboratory, Oak Ridge, TN, USA

    Arthur ‘Barney’ Maccabe

  3. Oak Ridge National Laboratory, Oak Ridge, TN, USA

    James Nutaro

  4. Oak Ridge National Laboratory, Oak Ridge, TN, USA

    Swaroop Pophale

  5. Oak Ridge National Laboratory, Oak Ridge, TN, USA

    Pravallika Devineni

  6. Oak Ridge National Laboratory, Oak Ridge, TN, USA

    Theresa Ahearn

  7. Oak Ridge National Laboratory, Oak Ridge, TN, USA

    Becky Verastegui

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Glaser, J., Aramburú, F., Malpica, W., Hernández, B., Baker, M., Aramburú, R. (2022). Scaling SQL to the Supercomputer for Interactive Analysis of Simulation Data. In: Nichols, J., et al. Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation. SMC 2021. Communications in Computer and Information Science, vol 1512. Springer, Cham. https://doi.org/10.1007/978-3-030-96498-6_19

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  • DOI: https://doi.org/10.1007/978-3-030-96498-6_19

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