A framework for generating task parallel programs

We consider the generation of mixed task and data parallel programs and discuss how a clear separation into a task and data parallel level can support the development of efficient programs. The program development starts with a specification of the maximum degree of task and data parallelism and proceeds by performing several derivation steps in which the degree of parallelism is adapted to a specific parallel machine. We show how the final message-passing programs are generated and how the interaction between the task and data parallel levels can be established. We demonstrate the usefulness of the approach by examples from numerical analysis which offer the potential of a mixed task and data parallel execution but for which it is not a priori clear, how this potential should be used for an implementation on a specific parallel machine.