MGB水文模型的顶线分析与性能优化

H. Freitas, C. Mendes
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引用次数: 2

摘要

rooline模型提供了关于受内存或处理器限制的应用程序的性能行为的见解,为性能改进提供了有用的指导。本研究使用rooline模型对模拟大尺度流域水文过程的MGB模型进行分析。实际输入数据用于描述两个多核架构上的性能,一个只有cpu,一个有cpu /GPU。MGB模型的性能通过更好的内存使用优化,以及共享内存(OpenMP)和GPU (OpenACC)并行性得到改善。CPU性能达到每个系统峰值的42.51%和50.17%,而GPU性能由于MGB模型结构引起的开销而较低。
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Roofline Analysis and Performance Optimization of the MGB Hydrological Model
The Roofline model gives insights about the performance behavior of applications bounded by either memory or processor limits, providing useful guidelines for performance improvements. This work uses the Roofline model on the analysis of the MGB model that simulates hydrological processes in largescale watersheds. Real-world input data are used to characterize the performance on two multicore architectures, one with only CPUs and one with CPUs/GPU. The MGB model performance is improved with optimizations for better memory use, and also with shared-memory (OpenMP) and GPU (OpenACC) parallelism. CPU performance achieves 42.51 % and 50.17 % of each system’s peak, whereas GPU performance is low due to overheads caused by the MGB model structure.
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