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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 scalable, 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 GRIDGUM2 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
Concurrent, distributed, and parallel languages, Grid Computing, Functional Languages

G. J. Michaelson, P. W. Trinder, H. Loidl and A. D. Al Zain, "Evaluating a High-Level Parallel Language (GpH) for Computational GRIDs," in IEEE Transactions on Parallel & Distributed Systems, vol. 19, no. , pp. 219-233, 2007.
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