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Effect of the storage format of sparse linear systems on parallel CFD computations

机译:稀疏线性系统的存储格式对并行CFD计算的影响

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Implicit solutions of Computational Fluid Dynamics (CFD) problems require the iterative solution of very large systems of Nuations. This paper investigates the comparative costs of two storage formats for large sparse matrices, namely the Compressed sparse Row (CSR) and BSR storage formats, for various solution strategies. The block structure of the BSR storage format is highly advantageous in applications which have several degrees of freedom per nodal point, such as CFD calculations. Depending on the solution strategy, overall reductions in both CPU time and memory can be as high as 30-50 /100. Such gains are especially appreciable in large 3D flow calculations.
机译:计算流体动力学(CFD)问题的隐式解决方案需要非常大的Nuations系统的迭代解决方案。本文研究了针对各种稀疏矩阵的两种稀疏矩阵存储格式的比较成本,即压缩稀疏行(CSR)和BSR存储格式。 BSR存储格式的块结构在每个节点具有多个自由度的应用(例如CFD计算)中具有很高的优势。根据解决方案策略的不同,CPU时间和内存的总体减少幅度可能高达30-50 / 100。在大型3D流量计算中,这种增益尤其明显。

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