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The Discrete Operator Approach to the Numerical Solution of Partial Differential Equations

机译:偏微分方程数值解的离散算子方法

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The design of robust computational physics codes has always been a challenge to application programmers. One of the key difficulties in writing multiphysics codes stems from the inefficient handling of spatial discretization and field operations. For example, in the context of the finite volume (FV) method, one often deals with structured and unstructured meshes that are either staggered or collocated. To handle this array of options, a complex data structure is required to represent arbitrary meshes. For structured grids, this approach imposes an unnecessary computational overhead that increases significantly with problem size. Instead, the programmer must write specific components to handle structured meshes thus defeating the purpose of code portability. Furthermore, dedicated discretization schemes are required for different types of meshes, thus increasing software complexity. Although modern computational codes rely extensively on a variety of libraries for linear algebra operations, they lack a framework that provides proper application-independent discretization tools. In this manuscript, we present a novel computational paradigm that separates the spatial discretization and -field operations from the physics. This paradigm is based on the abstraction of the mathematical operators describing physical processes. An operator corresponds to a precise mathematical object that performs a certain calculation on a field. A field corresponds to any scalar or vector variable required in the solution process. In our model, an operator is represented discretely by a sparse matrix while a field is represented by a vector. At the outset, the discretization process corresponds to a sparse-matrix-vector multiplication. This approach completely decouples the physics from the spatial and field operations thus providing an avenue for improved code design and usability.
机译:健壮的计算物理代码的设计一直是应用程序程序员的一项挑战。编写多物理场代码的主要困难之一是对空间离散化和野外作业的低效率处理。例如,在有限体积(FV)方法的上下文中,通常处理交错或并置的结构化和非结构化网格。要处理此选项数组,需要使用复杂的数据结构来表示任意网格。对于结构化网格,此方法施加了不必要的计算开销,该开销随着问题的大小而显着增加。相反,程序员必须编写特定的组件来处理结构化网格,从而无法实现代码可移植性的目的。此外,不同类型的网格需要专用的离散化方案,因此增加了软件复杂性。尽管现代计算代码在很大程度上依赖于各种用于线性代数运算的库,但是它们缺乏提供适当的独立于应用程序的离散化工具的框架。在这份手稿中,我们提出了一种新颖的计算范式,它将空间离散化和场操作与物理学分开。该范例基于描述物理过程的数学运算符的抽象。运算符对应于在字段上执行特定计算的精确数学对象。字段对应于求解过程中所需的任何标量或矢量变量。在我们的模型中,一个运算符由一个稀疏矩阵离散表示,而一个场则由一个矢量表示。首先,离散化过程对应于稀疏矩阵向量乘法。这种方法使物理与空间和现场操作完全脱钩,从而提供了改进代码设计和可用性的途径。

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