Experiences with CODE and HeNCE in Visual Programming for Parallel Computing

Visual programming has particular appeal for explicit parallel programming, particularly coarse grain MIMD programming. Explicitly parallel programs are multi-dimensional objects; the natural representations of a parallel program are annotated directed graphs: data flow graphs, control flow graphs, etc. where the nodes of the graphs are sequential computations. A visually based (directed graph) representation of parallel programs is thus more natural than a pure text string language where multi-dimensional structures must be implicitly defined. The naturalness of the annotated directed graph representation of parallel programs enables methods for programming and debugging which are qualitatively different and arguably superior to the conventional practice based on pure text string languages. Two visually-oriented parallel programming systems, CODE 2.0 and HeNCE, will be used to illustrate these concepts. The benefits of visually-oriented realizations of these models for program structure capture, performance analysis and debugging will be explored. It is only by actually implementing and using visual parallel programming languages that we have been able to fully evaluate their merits.

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