Basic HTML version of Foils prepared 13 February 2000

Foil 35 Data-Parallel Languages

From Methodology of Computational Science CPS615 Computational Science -- Spring Semester 2000. by Geoffrey C. Fox


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



© Northeast Parallel Architectures Center, Syracuse University, npac@npac.syr.edu

If you have any comments about this server, send e-mail to webmaster@npac.syr.edu.

Page produced by wwwfoil on Thu Mar 16 2000