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Scaling Productivity and Innovation on the Path to Exascale with a “Team of Teams” Approach

  • Elaine M. RaybournEmail author
  • J. David Moulton
  • Aimee Hungerford
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11589)

Abstract

One of the core missions of the Department of Energy (DOE) is to move beyond current high performance computing (HPC) capabilities toward a capable exascale computing ecosystem that accelerates scientific discovery and addresses critical challenges in energy and national security. The very nature of this mission has drawn a wide range of talented and successful scientists to work together in new ways to push beyond the status-quo toward this goal. For many scientists, their past success was achieved through efficient and agile collaboration within small trusted teams that rapidly innovate, prototype, and deliver. Thus, a key challenge for the ECP (Exascale Computing Project) is to scale this efficiency and innovation from small teams to aggregate teams of teams. While scaling agile collaboration from small teams to teams of teams may seem like a trivial transition, the path to exascale introduces significant uncertainty in HPC scientific software development for future modeling and simulation, and can cause unforeseen disruptions or inefficiencies that impede organizational productivity and innovation critical to achieving an integrated exascale vision. This paper identifies key challenges in scaling to a team of teams approach and recommends strategies for addressing them. The scientific community will take away lessons learned and recommended best practices from examples for enhancing productivity and innovation at scale for immediate use in modeling and simulation software engineering projects and programs.

Keywords

High performance computing (HPC) Exascale Team of teams Computational science & engineering (CSE) VUCA Organizational productivity 

Notes

Acknowledgements

*Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525. Images in Figs. 1 and 2 copyright by NTESS LLC and reproduced with permission. **This work was supported by the U.S. Department of Energy Office of Science, Office of Advanced Scientific Computing Research (ASCR), Office of Biological and Environmental Research (BER), and by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration. Figure 3 reproduced with permission. Special thanks to the ADTM-ASC Ristra project for their willingness to be highlighted as an exemplar for the approach, challenges, and successes discussed in the present paper.

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Copyright information

© National Technology & Engineering Solutions of Sandia, LLC. Under the terms of Contract DE-NA0003525, there is a non-exclusive license for use of this work by or on behalf of the U.S. Government 2019

Authors and Affiliations

  • Elaine M. Raybourn
    • 1
    Email author
  • J. David Moulton
    • 2
  • Aimee Hungerford
    • 2
  1. 1.Sandia National LaboratoriesAlbuquerqueUSA
  2. 2.Los Alamos National LaboratoriesLos AlamosUSA

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