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Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI

17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, Oak Ridge, TN, USA, August 26-28, 2020, Revised Selected Papers

  • Conference proceedings
  • © 2020

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Editors:
  1. Jeffrey Nichols

    1. Oak Ridge National Laboratory, Oak Ridge, USA

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  2. Becky Verastegui

    1. Oak Ridge National Laboratory, Oak Ridge, USA

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  3. Arthur ‘Barney’ Maccabe

    1. Oak Ridge National Laboratory, Oak Ridge, USA

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  4. Oscar Hernandez

    1. Oak Ridge National Laboratory, Oak Ridge, USA

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  5. Suzanne Parete-Koon

    1. Oak Ridge National Laboratory, Oak Ridge, USA

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  6. Theresa Ahearn

    1. Oak Ridge National Laboratory, Oak Ridge, USA

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Part of the book series: Communications in Computer and Information Science (CCIS, volume 1315)

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Conference proceedings info: SMC 2020.

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Table of contents (38 papers)

  1. Front Matter

    Pages i-xvii
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  2. Computational Applications: Converged HPC and Artificial Intelligence

    1. Front Matter

      Pages 1-1
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    2. Improving Seismic Wave Simulation and Inversion Using Deep Learning

      • Lei Huang, Edward Clee, Nishath Ranasinghe
      Pages 3-19

    3. Large-Scale Neural Solvers for Partial Differential Equations

      • Patrick Stiller, Friedrich Bethke, Maximilian Böhme, Richard Pausch, Sunna Torge, Alexander Debus et al.
      Pages 20-34

    4. Integrating Deep Learning in Domain Sciences at Exascale

      • Rick Archibald, Edmond Chow, Eduardo D’Azevedo, Jack Dongarra, Markus Eisenbach, Rocco Febbo et al.
      Pages 35-50

    5. Improving the Performance of the GMRES Method Using Mixed-Precision Techniques

      • Neil Lindquist, Piotr Luszczek, Jack Dongarra
      Pages 51-66

    6. On the Use of BLAS Libraries in Modern Scientific Codes at Scale

      • Harry Waugh, Simon McIntosh-Smith
      Pages 67-79

  3. System Software: Data Infrastructure and Life Cycle

    1. Front Matter

      Pages 81-81
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    2. A Systemic Approach to Facilitating Reproducibility via Federated, End-to-End Data Management

      • Dale Stansberry, Suhas Somnath, Gregory Shutt, Mallikarjun Shankar
      Pages 83-98

    3. Fulfilling the Promises of Lossy Compression for Scientific Applications

      • Franck Cappello, Sheng Di, Ali Murat Gok
      Pages 99-116

    4. DataStates: Towards Lightweight Data Models for Deep Learning

      • Bogdan Nicolae
      Pages 117-129

    5. Scalable Data-Intensive Geocomputation: A Design for Real-Time Continental Flood Inundation Mapping

      • Yan Y. Liu, Jibonananda Sanyal
      Pages 130-144

    6. Enabling Scientific Discovery at Next-Generation Light Sources with Advanced AI and HPC

      • Nicholas Schwarz, Stuart Campbell, Alexander Hexemer, Apurva Mehta, Jana Thayer
      Pages 145-156

    7. Visualization as a Service for Scientific Data

      • David Pugmire, James Kress, Jieyang Chen, Hank Childs, Jong Choi, Dmitry Ganyushin et al.
      Pages 157-174

    8. Performance Improvements on SNS and HFIR Instrument Data Reduction Workflows Using Mantid

      • William F. Godoy, Peter F. Peterson, Steven E. Hahn, John Hetrick, Mathieu Doucet, Jay J. Billings
      Pages 175-186

  4. Experimental/Observational Applications: Use Cases That Drive Requirements for AI and HPC Convergence

    1. Front Matter

      Pages 187-187
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    2. Software Framework for Federated Science Instruments

      • Thomas Naughton, Seth Hitefield, Lawrence Sorrillo, Nageswara Rao, James Kohl, Wael Elwasif et al.
      Pages 189-203

    3. Automated Integration of Continental-Scale Observations in Near-Real Time for Simulation and Analysis of Biosphere–Atmosphere Interactions

      • David J. Durden, Stefan Metzger, Housen Chu, Nathan Collier, Kenneth J. Davis, Ankur R. Desai et al.
      Pages 204-225

    4. Toward Real-Time Analysis of Synchrotron Micro-Tomography Data: Accelerating Experimental Workflows with AI and HPC

      • James E. McClure, Junqi Yin, Ryan T. Armstrong, Ketan C. Maheshwari, Sean Wilkinson, Lucas Vlcek et al.
      Pages 226-239

    5. Unsupervised Anomaly Detection in Daily WAN Traffic Patterns

      • Scott Campbell, Mariam Kiran, Fatema Bannat Wala
      Pages 240-256
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  1. Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI

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About this book

This book constitutes the revised selected papers of the 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, held in Oak Ridge, TN, USA*, in August 2020.

The 36 full papers and 1 short paper presented were carefully reviewed and selected from a total of 94 submissions. The papers are organized in topical sections of computational applications: converged HPC and artificial intelligence; system software: data infrastructure and life cycle; experimental/observational applications: use cases that drive requirements for AI and HPC convergence; deploying computation: on the road to a converged ecosystem; scientific data challenges.

*The conference was held virtually due to the COVID-19 pandemic.

Editors and Affiliations

  • Oak Ridge National Laboratory, Oak Ridge, USA

    Jeffrey Nichols, Becky Verastegui, Arthur ‘Barney’ Maccabe, Oscar Hernandez, Suzanne Parete-Koon, Theresa Ahearn

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