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Title: DOE Advanced Scientific Computing Advisory Subcommittee (ASCAC) Report: Top Ten Exascale Research Challenges

Program Document ·
DOI:https://doi.org/10.2172/1222713· OSTI ID:1222713
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  1. University of Southern California, Information Sciences Institute
  2. Sandia National Laboratories
  3. Columbia University
  4. Intel
  5. Institute for Defense Analyses
  6. University of California, San Diego
  7. IBM
  8. DARPA
  9. NVIDIA
  10. University of Tennessee
  11. Oak Ridge National Laboratory
  12. Lawrence Livermore National Laboratory
  13. Pacific Northwest National Laboratory
  14. University of Notre Dame
  15. Reservoir Labs
  16. Rice University
  17. Hewlett Packard
  18. Lawrence Berkeley National Laboratory
  19. Indiana University
  20. Argonne National Laboratory
  21. Science and Technology Associates
  22. Los Alamos National Laboratory

Exascale computing systems are essential for the scientific fields that will transform the 21st century global economy, including energy, biotechnology, nanotechnology, and materials science. Progress in these fields is predicated on the ability to perform advanced scientific and engineering simulations, and analyze the deluge of data. On July 29, 2013, ASCAC was charged by Patricia Dehmer, the Acting Director of the Office of Science, to assemble a subcommittee to provide advice on exascale computing. This subcommittee was directed to return a list of no more than ten technical approaches (hardware and software) that will enable the development of a system that achieves the Department's goals for exascale computing. Numerous reports over the past few years have documented the technical challenges and the non¬-viability of simply scaling existing computer designs to reach exascale. The technical challenges revolve around energy consumption, memory performance, resilience, extreme concurrency, and big data. Drawing from these reports and more recent experience, this ASCAC subcommittee has identified the top ten computing technology advancements that are critical to making a capable, economically viable, exascale system.

Research Organization:
USDOE Office of Science (SC) (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
OSTI ID:
1222713
Country of Publication:
United States
Language:
English