This thesis presents a combination of p-independent and p-dependent extensions to ZPL.

Gather and scatter are data redistribution functions of longstanding 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. Categories and Subject Descriptors D.3.2 [Programming Languages]: Language Classifications—concurrent, distributed and parallel languages

An import issue for numerical weather prediction modes (NWP) is the time it takes to produce a valid forecast. One factor, which greatly influences this simulation time is the size of the time step. However, time step size is often limited by the numerical stability of the used advection schemes. Available schemes include semiimplicit Eulerian and semi-Lagrangian schemes. In principal, semi-Lagrangian formulations result in irregular communications on parallel architectures. In this paper we describe automatic code generation for a semi-implicit scheme with a semi-Lagrangian formulation. We describe how code can be generated from a mathematical specification of the advection model, the embedding of the formulations in the CTADEL code generation tool and we show the parallelization of the code. Finally, we show results from preliminary experiments we have conducted with the generated code and the reference code from a production NWP on a number of different architectures.

This paper suggests that data parallelism is more general than previously thought and that integrating support for task parallelism into a data parallel programming language is a mistake. With several proposed improvements, the data parallel programming language ZPL is surprisingly versatile. The language and its power are illustrated by the solution to several traditionally task parallel problems. In addition, limitations are discussed.