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Foil 40 Data-Parallel Languages

From Master Foilset for CPS615 Introduction -- Material from Culler and Koelbel Computational Science for Simulations -- Fall Semester 1998. by Geoffrey C. Fox, Nancy McCracken


Data-parallel languages provide an abstract, machine-independent model of parallelism.
  • Fine-grain parallel operations, such as element-wise operations on arrays
  • Shared data in large, global arrays with mapping "hints"
  • Implicit synchronization between operations
  • Partially explicit communication from operation definitions
Advantages:
  • Global operations conceptually simple
  • Easy to program (particularly for certain scientific applications)
Disadvantages:
  • Unproven compilers
  • As express "problem" can be inflexible if new algorithm which language didn't express well
Examples: HPF, C*, HPC++
Originated on SIMD machines where parallel operations are in lock-step but generalized (not so successfully as compilers too hard) to MIMD



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