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Parallel Schur complement method for large-scale systems on distributed memory computers

机译:分布式内存计算机上大规模系统的并行Schur补码方法

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The Schur complement method, also known as substructuring technique, was widely used in structural mechanics to solve large-scale systems with limited memory computers for more than three decades [J.S. Przemieniecki, AIAA J. 1 (1963) 138]. Currently, due to developments in computer technology, the available on-board memory has increased considerably. Despite the existence of these high-memory systems, the Schur complement method still finds its ap- plications in structural mechanics through parallel computing. When developing a computer program, the Schur method has a significant book-keeping load in comparison to other parallel algorithms used, e.g., Schwarz alternating domain decomposition method [H.A. Schwarz, Gesammelte Mathematiche Abhandlungen, vol. 2, Springer, Berlin, 1890, p. 133]. This results in memory usage. Although parallel systems are used, global coefficient matrices require a large amount of memory. Therefore, significant memory is reserved for the solution of large-scale systems. In this paper, we present an efficient algorithm for the assemblage and solution of interface equations which facilitates the solution of large-scale systems via the Schur complement method on multiple instruction multiple data (MIMD) distributed memory architectures. In this method, we assemble the subdomain and interface coefficient matrices in such a manner that the memory requirements decrease significantly, resulting in the solution of large-scale systems with reasonable memory usage. The computer program is tested on distributed memory architectures with UNIX, WINDOWS NT, and LINUX operating systems.
机译:舒尔(Schur)补码法(又称子构造技术)在结构力学中被广泛使用,以解决具有有限内存计算机的大型系统已有三十多年的历史了。 Przemieniecki,AIAA J. 1(1963)138]。当前,由于计算机技术的发展,可用的板载存储器已大大增加。尽管存在这些高内存系统,但Schur补码方法仍然可以通过并行计算在结构力学中找到其应用。与使用的其他并行算法(例如Schwarz交替域分解方法)相比,Schur方法在开发计算机程序时具有很大的簿记负担。 Schwarz,Gesammelte Mathematiche Abhandlungen,第一卷。 2,施普林格,柏林,1890年,第1页。 133]。这导致内存使用。尽管使用并行系统,但是全局系数矩阵需要大量的内存。因此,为大型系统的解决方案保留了大量内存。在本文中,我们为接口方程的组合和求解提供了一种有效的算法,该算法可通过Schur补码方法在多指令多数据(MIMD)分布式存储体系结构上简化大规模系统的求解。在这种方法中,我们以使内存需求显着减少的方式组装子域和接口系数矩阵,从而得出具有合理内存使用率的大规模系统的解决方案。该计算机程序已在使用UNIX,WINDOWS NT和LINUX操作系统的分布式内存体系结构上进行了测试。

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