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Leadership Computing Platforms, Extreme-scale Applications, and Performance Strategies

by John Mellor-Crummey last modified 2012-08-04 05:06

July 23 - 26, 2012, Snowbird Ski & Summer Resort, Snowbird, UT, USA

Organizers

  • Rusty Lusk (Argonne National Lab), "lusk" AT "mcs.anl.gov"
  • Pete Beckman (Argonne National Lab), "beckman" AT "mcs.anl.gov"


Abstract


Goals:
  • Become familiar with the architecture, operation, and usability issues for each of the DOE Leadership Class Facilities.
  • Understand application scaling bottlenecks on the systems.
  • Learn strategies for achieving good performance with message passing and I/O libraries.
  • Explore new programming models, languages, and techniques that can provide scalable performance.
  • Learn the tools and suggest strategies for understanding the performance of petascale applications.


Final Agenda

Monday, July 23

Morning
Afternoon
Evening
  • 6:30-8:00: Dinner buffet provided


Tuesday, July 24

Morning Afternoon Evening
  • 6:30 - 8:00: Dinner buffet provided
  • 8:00 - ???: Late Night hacking: study codes and challenges.


Wednesday, July 25

Morning
  • 7:00 - 8:30: Breakfast buffet provided
  • 8:30 - 10:30: Yonghong Yan: OpenMP
  • 10:30 - 11:00: Break
  • 11:00 - 12:30: Wyatt Spear: TAU Performance System
Afternoon
  • 12:30 - 1:30: Lunch buffet provided
  • 1:30 - 02:00: Yonghong Yan: OpenACC
  • 2:00 - 6:00: Hands on work with MPI, performance tools, MPI-IO, ...
Evening
  • 6:30 - 8:00: Dinner Provided
  • 8:00 - ???: Late night hacking: continue collaborative work


Thursday, July 26

Morning
Afternoon
  • 12:30 - 2:00: Lunch Provided
  • 2:00 - 5:30: Hands on work with MPI, performance tools, MPI-IO, ...
  • 5:30 - 6:00: Final discussion and workshop wrap-up
Evening
  • Dinner
  • 6:30 - 8:00: Dinner buffet provided
  • 8:30 - ???: Late night hacking: continue collaborative work


Friday, July 27

Departure day

Sponsors

This workshop is sponsored by the Center for Scalable Application Development Software, with funding from the DOE Office of Science through the Scientific Discovery through Advanced Computing (SciDAC) program.

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CScADS Collaborators include:

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