Multi-GPU Implementation of the NICAM Atmospheric Model
Multi-GPU Implementation of the NICAM Atmospheric Model
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DOI：
10.1007/978-3-642-36949-0_20
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发表时间：
2012-08
期刊：
影响因子：
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通讯作者：
I. Demeshko;N. Maruyama;H. Tomita;S. Matsuoka
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文献类型：
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作者：
I. Demeshko;N. Maruyama;H. Tomita;S. Matsuoka
气候模拟模式用于解决各种科学问题，气候预测的准确性主要受模式分辨率的限制。更精细的分辨率导致更准确的预测，但同时也显著增加了计算复杂性。这就解释了人们对高性能计算（HPC），尤其是GPU计算，对气候模拟越来越感兴趣的原因。提出了一种在多gpu环境下高效实现非流体静力二十面体大气模型（NICAM）的方法。我们已经获得了gpu数量达到320的性能结果。这些结果与并行CPU版本进行了比较，表明我们的GPU实现比并行CPU版本的性能提高了3倍。我们还开发并验证了NICAM的全gpu实现的性能模型。结果显示，与并行CPU版本相比，可能有4.5倍的加速。我们相信我们的结果是通用的，因为在类似的应用程序中，我们可以实现类似的加速，并且有能力预测其在cpu上的程度。
Climate simulation models are used for a variety of scientific problems and accuracy of the climate prognoses is mostly limited by the resolution of the models. Finer resolution results in more accurate prognoses but, at the same time, significantly increases computational complexity. This explains the increasing interest to the High Performance Computing (HPC), and GPU computations in particular, for the climate simulations. We present an efficient implementation of the Nonhydrostatic ICosahedral Atmospheric Model (NICAM) on the multi-GPU environment. We have obtained performance results for the number of GPUs up to 320. These results were compared with the parallel CPU version and demonstrate that our GPU implementation gives 3 times higher performance over parallel CPU version. We have also developed and validated the performance model for a full-GPU implementation of the NICAM. Results show 4.5x potential acceleration over parallel CPU version. We believe that our results are general, in that in similar applications we could achieve similar speedups, and have the ability to predict its degree over CPUs.