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Workshop on Leadership-class Machines, Petascale Applications, and Performance Strategies

by admin last modified 2010-07-22 08:36

July 19–22, 2010, Snowbird Ski & Summer Resort, Snowbird, Utah, 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

Day 1 - Monday, July 19

Morning Afternoon Evening
  • 6:30-8:00: Dinner Provided


Day 2 - Tuesday, July 20

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


Day 3 - Wednesday, July 21

Morning Afternoon
  • 12:00 - 1:30: Lunch Provided
  • 1:30 - 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


Day 4 - Thursday, July 22

Morning
  • 7:00 - 8:30: Breakfast Buffet Provided
  • 8:30 - 10:00: Rob Latham: Parallel I/O in Practice, part 1
  • 10:00 - 10:30: Break
  • 10:30 - 11:00: Rob Latham: Parallel I/O in Practice, part 2
  • 11:00 - 12:30: Tom Peterka: Visualization & Data Analysis

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 Provided
  • 8:30 - ???: Late night hacking: continue collaborative work


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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