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Initially there is just one communicator, known as MPI_COMM_WORLD, from which other communicators can be constructed through progressive “slicing” of the communication space. The decision to prohibit creating communicators from scratch provides additional guarantees of safety, though the specification does recognise it as a “chicken and egg” scenario [2]. Implementations The initial implementation of MPI was MPICH [50], a project which has demonstrated the application and scalability of MPI-1 on supercomputers and cluster platforms [51].

Let us quickly correlate the two pieces of code: • Lines 2 to 4 of the Haskell code define the formal parameter list of the CUDA kernel and its wrapper. This corresponds to lines 1 and 13 in the generated code. • Lines 8 to 9 declare local variables for holding one element of each of the two streams. These declarations appear in lines 5 and 6 of the generated code. • Line 11 inserts the code that represents the function, f, that was passed to zipWithS. In this case f is the function (+), and this is reflected in line 7 of the CUDA kernel code.

2. The sequence in which worksharing regions are encountered must be identical for all threads in a team. By default a work sharing region mirrors the parallel construct in that there is an implicit barrier upon its completion. This can however be removed (using the nowait clause), allowing threads which complete early to continue executing code within their enclosing region. Data Environment The data environment directives provided by OpenMP allow the control of data visibility and access within a parallel region.

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