We have parallelized a grid-based weather forecast model called SEQN using two programming models: shared memory and message passing. By shared memory we mean programming in standard Fortran 77 with directives for parallelism, such as is found on the Kendall Square Research KSR1 parallel supercomputer. For message passing we used the distributed memory Intel Paragon. We have benchmarked both versions of the code on the respective machines, and have run the message passing version on the KSR1 in order to directly compare performance and evaluate the cost of portability. In addition we present first results from the KSR2.
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机译：我们使用两个编程模型并行化了一个基于网格的天气预报模型SEQN，该模型称为SEQN：共享内存和消息传递。共享内存是指在标准Fortran 77中使用并行指令进行编程，例如在Kendall Square Research KSR1并行超级计算机上可以找到的指令。对于消息传递，我们使用了分布式内存Intel Paragon。我们已经在各自的机器上对这两个版本的代码进行了基准测试，并在KSR1上运行了消息传递版本，以便直接比较性能并评估可移植性的成本。此外，我们还展示了KSR2的初步结果。
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