Abstract

SAC is a purely functional array processing language designed with numerical applications in mind. It supports generic, high-level program specifications in the style of APL. However, rather than providing a fixed set of builtin array operations, SAC provides means to specify such operations in the language itself in a way that still allows their application to arrays of any dimension and size. This paper illustrates the specificational benefits of this approach by means of a high-level SAC implementation of the NAS benchmark MG realizing 3-dimensional multigrid relaxation with periodic boundary conditions.Despite the high-level approach, experiments show that by means of aggressive compiler optimizations SAC manages to achieve performance characteristics in the range of low-level Fortran and C implementations. For benchmark size class A, SAC is outperformed by the serial Fortran-77 reference implementation of the benchmark by only 23%, whereas SAC itself outperforms a C implementation by the same figure. Furthermore, implicit parallelization of the SAC code for shared memory multiprocessors achieves a speedup of 7.6 with 10 processors. With these figures, SAC outperforms both automatic parallelization of the serial Fortran-77 reference implementation as well as an OpenMP solution based on C code.

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