利用原子同步原始材料在一般有限元素应用中集中稀薄矩阵的灵活稀散矩阵数据格式和平行算法 (A flexible sparse matrix data format and parallel algorithms for the assembly of sparse matrices in general finite element applications using atomic synchronisation primitives)

稀疏 · Atom（文本编辑器） · Storage · Processing（编程语言） · Performer ·

2021 年 7 月 15 日

A flexible sparse matrix data format and parallel algorithms for the assembly of sparse matrices in general finite element applications using atomic synchronisation primitives

翻译：利用原子同步原始材料在一般有限元素应用中集中稀薄矩阵的灵活稀散矩阵数据格式和平行算法

Adam Sky,César Polindara,Ingo Muench,Carolin Birk

Finite element methods require the composition of the global stiffness matrix from local finite element contributions. The composition process combines the computation of element stiffness matrices and their assembly into the global stiffness matrix, which is commonly sparse. In this paper we focus on the assembly process of the global stiffness matrix and explore different algorithms and their efficiency on shared memory systems using C++. A key aspect of our investigation is the use of atomic synchronization primitives for the derivation of data-race free algorithms and data structures. Furthermore, we propose a new flexible storage format for sparse matrices and compare its performance with the compressed row storage format using abstract benchmarks based on common characteristics of finite element problems.

翻译：精度元素方法要求从本地的有限元素贡献中组成全球硬度矩阵。组成过程将元素硬度矩阵及其组装的计算综合到通常稀少的全球硬度矩阵中。在本文件中,我们侧重于全球硬度矩阵的组装过程,并探索不同的算法及其在使用C+++共享记忆系统方面的效率。我们调查的一个关键方面是利用原子同步原始元素来衍生数据-可选算法和数据结构。此外,我们提议为稀有矩阵采用新的灵活储存格式,并使用基于有限元素问题共同特征的抽象基准,将其性能与压缩行储存格式进行比较。