Visual Programming and Parallel Computing

Visual programming arguably provides greater benefit in explicit parallel programming, particularly coarse grain MIMD programming, than in sequential programming. Explicitly parallel programs are multi-dimenstioal 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. The execution of parallel programs is a directed graph of instances of 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. Annotation of the graphs is a critical element of a practical visual programming system; text is still the best way to represent many aspects of programs. This paper presents a model of parallel programming and a model of execution for parallel programs which are the conceptual framework for a complete visual programming environement including capture of parallel structure, compilation and behavior analysis (performance and debugging). Two visually-oriented parallel programming systems, CODE 2.0 and HeNCE, each based on a variant of the model of programming, will be used to illustrate the concepts. The benefits of visually-oriented realizations of these models for program structure capture, software component reuse, performance analysis and debugging will be explored and hopefully demonstated by examples in these representations. It is only by actually implementing and using visual parallel programming languages that we have been able to fully evaluate their merits.