Many implementations on message-passing machines can bene t from an exploitation of mixed task and data parallelism. A suitable parallel programming model is a group-SPMD model whic hrequires a structuring of the processors in to subsets and a partition of the program into multiprocessor tasks. In this paper, we i n troduce a library support for the speci cation of message-passing programs in a group-SPMD style allo wing di erent partitions in a single program. We describe the implementation of the library functions and illustrate the programming style.

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Many implementations on message-passing machines can benefit from an exploitation of mixed task and data parallelism. A suitable parallel programming model is a group-SPMD model, which requires a structuring of the processors into subsets and a partition of the program into multi-processor tasks. In this paper, we introduce a library support for the specification of message-passing programs in a group-SPMD style allowing different partitions in a single program. We describe the functionality and the implementation of the library functions and illustrate the library programming style with example programs. The examples show that the runtime on distributed memory machines can be considerably reduced by using the library.

SUMMARYMany programs for message-passing machines can benefit from an implementation in a group-SPMD programming model due to the potential to reduce communication overhead and to increase scalability. In this paper, we consider group-SPMD programs exploiting different orthogonal processor partitions in one program. For each program this is a fixed set of predefined processor partitions given by the parallel hyperplanes of a two-or multi-dimensional virtual processor organization. We introduce a library built on top of MPI to support the programming with those orthogonal processor groups. The parallel programming model is appropriate for applications with a multi-dimensional task grid and task dependencies mainly aligned in the dimensions of the task grid. The library can be used to specify the appropriate processor partitions, which are then created by the library, and to define the mapping of tasks to the processor hyperplanes. Examples from numerical analysis illustrate the programming style and show that the runtime on distributed memory machines can be considerably reduced by using the library.