Application%20Scaling

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Application Scaling
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Application Scaling

• Doug Kothe, ORNL
• Paul Muzio, CUNY
• Jonathan Carter, LLBL
• Bronis de Supinski, LLNL
• Mike Heroux, Sandia
• Phil Jones, LANL
• Brent Leback, The Portland Group
• Piyush Mehrotra, NASA Ames
• John Michalakes, NCAR
• Nir Paikowsky, ScaleMP
• Galen Shipman, ORNL
• Trey White, ORNL

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Application Scaling

• Are there more appropriate domain-specific
  performance metrics for science and engineering
  HPC applications available then the canonical
  percent of peak?
• Or parallel efficiency and scalability?
• If so, what are they?
• Are these metrics driving for weak or strong
  scaling or both?

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Application Scaling

• What is the role of local (node-based) floating
  point accelerators (e.g., cell, GPUs, etc.) for
  key science and engineering applications in the
  next 3-5 years?
• Is there unexploited or unrealized concurrency in
  the applications you are familiar with?
• If so, what, and where is it?

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Application Scaling

• Should applications continue with current
  programming models (Fortran, C, C, PGAS, etc.)
  and paradigms (e.g., flat MPI, hybrid MPI/OpenMP,
  etc.) over the next decade?
• If not, what needs to change?
• How might HPC system-attribute priorities change
  over the next decade for the science and
  engineering applications you are familiar with?

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Application Scaling

• Attributes to consider are
• node peak flops
• mean time to interrupt
• wide-area network bandwidth
• node memory capacity
• local storage capacity
• archival storage capacity
• memory latency
• interconnect latency
• disk latency
• interconnect bandwidth
• memory bandwidth
• disk bandwidth