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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 Scientific Discovery through Advanced Computing (SciDAC) program.

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