2D Simplified Wildfire Spreading Model in Python: From NumPy to CuPy

Daniel San Martín, Claudio Torres
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Abstract

Wildfires are a problem of great interest in the world because of the damage they cause every year to forest, wild fauna and flora, an also threatening human lives, among others. There are some computational models for numerical simulations to address this phenomena, and a few of them have an open-source implementation. The goal of this work is to extend a CPU Python’s implementation of wildfire open-source framework developed in NumPy, to a GPU improved version using CuPy. The algorithm used is based on a numerical discretization of a wildfire spreading mathematical model described by a system of partial differential equations. Computational and mathematical components, numerical simulations and applications are described in details in the document. In addition, this work includes includes a brief performance comparison between both implementations, pointing out that we can achieve good execution times using the CuPy GPU implementation without spending enough programming effort.
2D简化野火蔓延模型在Python:从NumPy到CuPy
野火是世界上非常感兴趣的问题,因为它们每年对森林、野生动植物造成破坏,也威胁着人类的生命等。有一些用于数值模拟的计算模型来处理这种现象,其中一些有开源实现。这项工作的目标是将CPU Python在NumPy中开发的wildfire开源框架的实现扩展到使用CuPy的GPU改进版本。所使用的算法是基于用偏微分方程组描述的野火蔓延数学模型的数值离散化。计算和数学组件,数值模拟和应用在文件中详细描述。此外,这项工作还包括两种实现之间的简短性能比较,指出我们可以使用CuPy GPU实现获得良好的执行时间,而无需花费足够的编程工作。
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