...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Computational Physics >A robust hierarchical solver for ill-conditioned systems with applications to ice sheet modeling
【24h】

A robust hierarchical solver for ill-conditioned systems with applications to ice sheet modeling

机译：一种强大的分层求解器，可用于冰贴模拟的应用程序

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

A hierarchical solver is proposed for solving sparse ill-conditioned linear systems in parallel. The solver is based on a modification of the LoRaSp method, but employs a deferred-compression technique, which provably reduces the approximation error and significantly improves efficiency. Moreover, the deferred-compression technique introduces minimal overhead and does not affect parallelism. As a result, the new solver achieves linear computational complexity under mild assumptions and excellent parallel scalability. To demonstrate the performance of the new solver, we focus on applying it to solve sparse linear systems arising from ice sheet modeling. The strong anisotropic phenomena associated with the thin structure of ice sheets creates serious challenges for existing solvers. To address the anisotropy, we additionally developed a customized partitioning scheme for the solver, which captures the strong-coupling direction accurately. In general, the partitioning can be computed algebraically with existing software packages, and thus the new solver is generalizable for solving other sparse linear systems. Our results show that ice sheet problems of about 300 million degrees of freedom have been solved in just a few minutes using 1024 processors. (C) 2019 Elsevier Inc. All rights reserved.
机译：提出了一种用于并行求解稀疏病态线性系统的分层求解器。该解算器基于对LoRaSp方法的修改，但采用了延迟压缩技术，这可以显著降低近似误差，并显著提高效率。此外，延迟压缩技术引入了最小的开销，并且不影响并行性。因此，新的求解器在温和的假设下实现了线性计算复杂度，并具有良好的并行可扩展性。为了演示新解算器的性能，我们重点将其应用于求解由冰盖建模产生的稀疏线性系统。与薄冰盖结构相关的强烈各向异性现象给现有的求解者带来了严峻的挑战。为了解决各向异性问题，我们还为解算器开发了一个定制的分区方案，该方案可以准确地捕捉强耦合方向。一般来说，分区可以用现有的软件包进行代数计算，因此新的求解器可推广用于求解其他稀疏线性系统。我们的结果表明，使用1024个处理器，大约3亿个自由度的冰盖问题在几分钟内就得到了解决。（C） 2019爱思唯尔公司版权所有。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号