In this paper, we present, evaluate and analyse the performance of parallel synchronous Jacobi algorithms by different partitioned procedures including band-row splitting, band-row sparsity pattern splitting and substructuring splitting, when solving sparse large linear systems. Numerical experiments performed on a set of academic 3D Laplace equation and on a real gravity matrices arising from the Chicxulub crater are exhibited, and show the impact of splitting on parallel synchronous iterations when solving sparse large linear systems. The numerical results clearly show the interest of substructuring methods compared to band-row splitting strategies.
翻译:在本文中,我们介绍、评价和分析平行同步的雅各比算法的性能,这些算法通过不同的分割程序,包括带-行分解、带-行宽模式分解和结构下分解等分解,在解决稀少的大型线性系统时。在一套学术性的3D Laplace方程式和由Chicxulub弹坑产生的真正重力矩阵上进行的数值实验被展示出来,并展示了在解决稀少的大型线性系统时分解对平行同步迭代的影响。数字结果清楚地表明了与带-行分解策略相比,低结构方法的兴趣。