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Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation

22nd Smoky Mountains Computational Sciences and Engineering Conference, SMC 2022, Virtual Event, August 23–25, 2022, Revised Selected Papers

  • Conference proceedings
  • © 2022

Overview

Editors:
  1. Kothe Doug

    1. Oak Ridge National Laboratory, Oak Ridge, USA

  2. Geist Al

    1. Oak Ridge National Laboratory, Oak Ridge, USA

  3. Swaroop Pophale

    1. Oak Ridge National Laboratory, Oak Ridge, USA

  4. Hong Liu

    1. Oak Ridge National Laboratory, Oak Ridge, USA

  5. Suzanne Parete-Koon

    1. Oak Ridge National Laboratory, Oak Ridge, USA

Part of the book series: Communications in Computer and Information Science (CCIS, volume 1690)

Included in the following conference series:

Conference proceedings info: SMC 2022.

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About this book

This book constitutes the refereed proceedings of the 22nd Smoky Mountains Computational Sciences and Engineering Conference on Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation, SMC 2022, held virtually, during August 23–25, 2022. 

The 24 full papers included in this book were carefully reviewed and selected from 74 submissions. They were organized in topical sections as follows: foundational methods enabling science in an integrated ecosystem; science and engineering applications requiring and motivating an integrated ecosystem; systems and software advances enabling an integrated science and engineering ecosystem; deploying advanced technologies for an integrated science and engineering ecosystem; and scientific data challenges.

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Table of contents (24 papers)

  1. Front Matter

    Pages i-xii
    Download chapter PDF

  2. Foundational Methods Enabling Science in an Integrated Ecosystem

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Computational Workflow for Accelerated Molecular Design Using Quantum Chemical Simulations and Deep Learning Models

      • Andrew E. Blanchard, Pei Zhang, Debsindhu Bhowmik, Kshitij Mehta, John Gounley, Samuel Temple Reeve et al.
      Pages 3-19

    3. Self-learning Data Foundation for Scientific AI

      • Annmary Justine, Sergey Serebryakov, Cong Xu, Aalap Tripathy, Suparna Bhattacharya, Paolo Faraboschi et al.
      Pages 20-37

    4. Preconditioners for Batched Iterative Linear Solvers on GPUs

      • Isha Aggarwal, Pratik Nayak, Aditya Kashi, Hartwig Anzt
      Pages 38-53

    5. Mobility Aware Computation Offloading Model for Edge Computing

      • Natnael Tefera, Ayalew Belay Habtie
      Pages 54-71

  3. Science and Engineering Applications Requiring and Motivating an Integrated Ecosystem

    1. Front Matter

      Pages 73-73
      Download chapter PDF

    2. Machine Learning for First Principles Calculations of Material Properties for Ferromagnetic Materials

      • Markus Eisenbach, Mariia Karabin, Massimiliano Lupo Pasini, Junqi Yin
      Pages 75-86

    3. A Vision for Coupling Operation of US Fusion Facilities with HPC Systems and the Implications for Workflows and Data Management

      • Sterling Smith, Emily Belli, Orso Meneghini, Reuben Budiardja, David Schissel, Jeff Candy et al.
      Pages 87-100

    4. At-the-Edge Data Processing for Low Latency High Throughput Machine Learning Algorithms

      • Jack Hirschman, Andrei Kamalov, Razib Obaid, Finn H. O’Shea, Ryan N. Coffee
      Pages 101-119

    5. Implementation of a Framework for Deploying AI Inference Engines in FPGAs

      • Ryan Herbst, Ryan Coffee, Nathan Fronk, Kukhee Kim, Kuktae Kim, Larry Ruckman et al.
      Pages 120-134

  4. Systems and Software Advances Enabling an Integrated Science and Engineering Ecosystem

    1. Front Matter

      Pages 135-135
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    2. Calvera: A Platform for the Interpretation and Analysis of Neutron Scattering Data

      • Gregory R. Watson, Gregory Cage, Jon Fortney, Garrett E. Granroth, Harry Hughes, Thomas Maier et al.
      Pages 137-154

    3. Virtual Infrastructure Twins: Software Testing Platforms for Computing-Instrument Ecosystems

      • Nageswara S. V. Rao, Anees Al-Najjar, Helia Zandi, Ramanan Sankaran, Susan Hicks, Kevin Roccapriori et al.
      Pages 155-172

    4. The INTERSECT Open Federated Architecture for the Laboratory of the Future

      • Christian Engelmann, Olga Kuchar, Swen Boehm, Michael J. Brim, Thomas Naughton, Suhas Somnath et al.
      Pages 173-190

    5. Real-Time Edge Processing During Data Acquisition

      • Max Rietmann, Praveen Nakshatrala, Jonathan Lefman, Geetika Gupta
      Pages 191-205

    6. Towards a Software Development Framework for Interconnected Science Ecosystems

      • Addi Malviya Thakur, Seth Hitefield, Marshall McDonnell, Matthew Wolf, Richard Archibald, Lance Drane et al.
      Pages 206-224

  5. Deploying Advanced Technologies for an Integrated Science and Engineering Ecosystem

    1. Front Matter

      Pages 225-225
      Download chapter PDF

    2. Adrastea: An Efficient FPGA Design Environment for Heterogeneous Scientific Computing and Machine Learning

      • Aaron R. Young, Narasinga Rao Miniskar, Frank Liu, Willem Blokland, Jeffrey S. Vetter
      Pages 227-243

    3. Toward an Autonomous Workflow for Single Crystal Neutron Diffraction

      • Junqi Yin, Guannan Zhang, Huibo Cao, Sajal Dash, Bryan C. Chakoumakos, Feiyi Wang
      Pages 244-256
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  1. Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation

Editors and Affiliations

  • Oak Ridge National Laboratory, Oak Ridge, USA

    Kothe Doug, Geist Al, Swaroop Pophale, Hong Liu, Suzanne Parete-Koon

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