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Comparison of shared memory and distributed memory parallelisation strategies for grid-based weather forecast models

机译:基于网格的天气预报模型的共享内存和分布式内存平行策略的比较

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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.
机译:我们已经并行化了一种基于网格的天气预报模型,使用两个编程模型:共享内存和消息传递。通过共享内存,我们的意思是标准Fortran 77中的编程,具有平行指令,例如在KENDALL Square Research KSR1并行超级计算机上找到。对于消息传递,我们使用了分布式内存Intel Paragon。我们在各个计算机上进行了基准测试的代码版本,并且在KSR1上运行了消息传递版本,以便直接比较性能并评估便携性的成本。此外,我们介绍了KSR2的第一个结果。

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