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Building an Integrated Ecosystem of Computational and Observational Facilities to Accelerate Scientific Discovery

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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

Future scientific discoveries will rely on flexible ecosystems that incorporate modern scientific instruments, high performance computing resources, parallel distributed data storage, and performant networks across multiple, independent facilities. In addition to connecting physical resources, such an ecosystem presents many challenges in logistics and accessibility, especially in orchestrating computations and experiments that span across leadership computing systems and experimental instruments. Past efforts have typically been application-specific or limited to interfaces for computing resources. This paper proposes a general framework for integrating computation resources and instrument operations, addressing challenges in code development/execution, data staging and collection, software stack, control mechanisms, resource authorization and governance, and hardware integration. We also describe a demonstration use case wherein a Bayesian optimization algorithm running on an edge computing resource guides a scanning probe microscope to autonomously and intelligently characterize a material sample. This science edge ecosystem framework will provide a blueprint for federating multi-institutional, disparate resources and orchestrating scientific workflows across them to enable next-generation discoveries.

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Acknowledgments

This research used resources of the Oak Ridge Leadership Computing Facility (OLCF) and Compute and Data Environment for Science (CADES) at the Oak Ridge National Laboratory (ORNL), and also supported by Robust Analytic Models for Science at Extreme Scales (RAMSES) project, all supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. It is also supported by Laboratory Directed Research and Development (LDRD) project at ORNL. A portion of this work was conducted at and supported (RKV, SJ, SVK) by the Center for Nanophase Materials Sciences, ORNL, a US DOE Office of Science User Facility.

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Authors and Affiliations

  1. Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA

    Suhas Somnath, Rama K. Vasudevan, Stephen Jesse, Sergei Kalinin, Nageswara Rao, Christopher Brumgard, Feiyi Wang, Olga Kuchar, Arjun Shankar, Ben Mintz, Elke Arenholz, J. Robert Michael & Sarp Oral

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  1. Suhas Somnath
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  2. Rama K. Vasudevan
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  3. Stephen Jesse
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Corresponding author

Correspondence to Suhas Somnath .

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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Somnath, S. et al. (2022). Building an Integrated Ecosystem of Computational and Observational Facilities to Accelerate Scientific Discovery. 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_4

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  • DOI: https://doi.org/10.1007/978-3-030-96498-6_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-96497-9

  • Online ISBN: 978-3-030-96498-6

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