The design and implementation of a parallel array operator for the arbitrary remapping of data

Gather and scatter are data redistribution functions of long-standing importance to high performance computing. In this paper, we present a highly-general array operator with powerful gather and scatter capabilities unmatched by other array languages. We discuss an efficient parallel implementation, introducing three new optimizations---schedule compression, dead array reuse, and direct communication---that reduce the costs associated with the operator's wide applicability. In our implementation of this operator in ZPL, we demonstrate performance comparable to the hand-coded Fortran + MPI versions of the NAS FT and CG benchmarks.