GroMoPo Metadata for Apuae basin GPGPU model

The application of computer simulation models plays a significant role in the understanding of water dynamics in basins. The recent and explosive growth of the processing capabilities of General-Purpose Graphics Processing Units (GPGPUs) has resulted in widespread interest in parallel computing from the modelling community. In this paper, we present a GPGPU implementation of finite-differences solution of the equations of the 2D groundwater flow in unconfined aquifers for heterogeneous and anisotropic media. We show that the GPGPU-accelerated solution implemented using CUDA(1) C/C++ largely outperforms the corresponding serial solution in C/Cthornthorn. The results show that the GPGPU-accelerated implementation is capable of providing up to a 56-fold speedup in the solution using an ordinary office computer equipped with an inexpensive GPU(2) card. The code developed for this research is available for download and use at http://modelagemambientaluffs.blogspot.com.br/. (C) 2017 Elsevier Ltd. All rights reserved.
Note: Bounding box set based on locaiton of Brazil generally since exact location unknown.

计算机仿真模型的应用，对于理解流域水动力过程具有重要意义。近年来，通用图形处理器（General-Purpose Graphics Processing Units，GPGPU）的计算性能实现爆发式增长，引发了建模领域对并行计算的广泛关注。本文针对非均质各向异性介质中的二维潜水含水层地下水流方程，提出了一种基于GPGPU的有限差分解法实现方案。研究表明，采用CUDA(1)的C/C++语言实现的GPGPU加速解法，其性能远优于基于C/Cthornthorn的串行对应解法。实验结果显示，在搭载入门级GPU(2)显卡的普通办公电脑上，该GPGPU加速实现方案可实现最高56倍的求解加速比。本研究开发的代码可在http://modelagemambientaluffs.blogspot.com.br/ 下载并使用。©2017 Elsevier Ltd. 版权所有。注：由于精确位置未知，边界框的设置总体基于巴西的地理位置。