The Utah Energy Balance (UEB) model supports gridded simulation of snow processes over a watershed. To enhance computational efficiency, we developed two parallel versions of the model, one using the Message Passing Interface (MPI) and the other using NVIDIA's CUDA code on Graphics Processing Unit (GPU). Evaluation of the speed-up and efficiency of the MPI version shows that the effect of input/output (IO) operations on the parallel model performance increases as the number of processor cores increases. As a result, although the computation kernel scales well with the number of cores, the efficiency of the parallel code as a whole degrades. The performance improves when the number of IO operations is reduced by reading/writing larger data arrays. The CUDA GPU implementation was done without major refactoring of the original UEB code, and tests demonstrated that satisfactory performance could be obtained without a major re-work of the existing UEB code.

犹他州能源平衡（UEB）模型支持分水岭上雪过程的网格化模拟。为了提高计算效率，我们开发了该模型的两个并行版本，一个使用消息传递接口（MPI），另一个使用图形处理单元（GPU）上的NVIDIA CUDA代码。对MPI版本的提速和效率的评估表明，输入/输出（IO）操作对并行模型性能的影响随着处理器内核数量的增加而增加。结果，尽管计算内核随核的数量而很好地扩展，但是并行代码的整体效率却降低了。通过读取/写入较大的数据阵列减少IO操作的数量时，性能会提高。无需大量重构原始UEB代码即可完成CUDA GPU的实现，