Parallel Application Paradigms CS433 Spring 2001

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Parallel Application ParadigmsCS433Spring 2001

• Laxmikant Kale

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Now that we know about the prog. Models...

• Programming models
• SAS, MPI, Charm, .
• What are the implications for what kinds of
  machines to build?
• Can we compare the models to decide which one is
  better?
• Answers to both questions depend on the
  characteristics of the applications one programs
  on these machines.
• We will next study several classes of
  applications
• Often a real application will include a mixture
  of these
• However, years of experience allows us to attempt
  taxanomy

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Application paradigms

• Master-Slave
• Tree-structured, dynamic, computations
• Divide-and-conquer, state-space search,
  branch-and-bound, game-trees
• Physical Simulations continuum
• Largest class of parallel applications
• (Parallel Databases and Traction-processing
  systems?)
• Discrete event simulations
• Transaction processing

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Physical simulations

• Typical scenario
• Continuous physical domain
• e.g. interior of rocket, bridge, airplane-wing
  with air flowing around, global weather,
• Modeled by partial differential equations
• Study/predict either steady-state behavior or
  time-varying behavior
• Implicit or explicit timesteps
• Variations and subclasses
• Structured and unstructured meshes
• arrays vs graphs
• Dynamic behavior vs static
• Adaptive refinements
• Particles

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Master-slave

• May be called manager-workers
• One master process, and several slave processes
• Manager sends tasks to the workers
• worker return results to the master
• No other communication (esp. among workers)
• Examples
• SETI, graphics, coarse-grained multiple
  simulations,
• Issues
• Master may become a bottleneck
• grainsize control
• Load balancing
• Adaptive worker asks for work when they are
  idle
• Master assigns all pieces of work to slaves at
  the beginning
• Use a leash? Master assigns multiple pieces to
  workers,
• and sends new work as they complete