Computational Grids potentially offer low cost, readily available, and large-scale high-performance platforms. For the parallel execution of programs, however, computational GRIDs pose serious challenges: they are heterogeneous, and have hierarchical and often shared interconnects, with high and variable latencies between clusters. This paper investigates whether a programming language with high-level parallel coordination and a Distributed Shared Memory model (DSM) can deliver good, and

more »

... e, performance on a range of computational GRID configurations. The high-level language, Glasgow parallel Haskell (GpH), abstracts over the architectural complexities of the computational GRID, and we have developed GRID-GUM2, a sophisticated grid-specific implementation of GpH, to produce the first high-level DSM parallel language implementation for computational GRIDs. We report a systematic performance evaluation of GRID-GUM2 on combinations of high/low and homo/hetero-geneous computational GRIDs. We measure the performance of a small set of kernel parallel programs representing a variety of application areas, two parallel paradigms, and ranges of communication degree and parallel irregularity. We investigate GRID-GUM2's performance scalability on medium-scale heterogeneous and high-latency computational GRIDs, and analyse the performance with respect to the program characteristics of communication frequency and degree of irregular parallelism.