Critical to the scalability of parallel adaptive simulations are parallel control functions including load balancing, reduced inter-process communication and optimal data decomposition. In distributed meshes, many mesh-based applications frequently access neighborhood information for computational purposes which must be transmitted efficiently to avoid parallel performance degradation when the neighbors are on different processors. This article presents a parallel algorithm of creating and deleting data copies, referred to as ghost copies, which localize neighborhood data for computation purposes while minimizing inter-process communication. The key characteristics of the algorithm are: (1) It can create ghost copies of any permissible topological order in a 1D, 2D or 3D mesh based on selected adjacencies. (2) It exploits neighborhood communication patterns during the ghost creation process thus eliminating all-to-all communication. (3) For applications that need neighbors of neighbors, the algorithm can create n number of ghost layers up to a point where the whole partitioned mesh can be ghosted. Strong and weak scaling results are presented for the IBM BG/P and Cray XE6 architectures up to a core count of 32,768 processors. The algorithm also leads to scalable results when used in a parallel super-convergent patch recovery error estimator, an application that frequently accesses neighborhood data to carry out computation.

中文翻译：

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柔性分布式网格数据库的并行重影算法

并行自适应功能的关键在于并行控制功能，这些功能包括负载平衡，减少的进程间通信和最佳的数据分解。在分布式网格中，出于计算目的，许多基于网格的应用程序经常访问邻域信息，这些邻域信息必须有效传输，以避免邻居在不同处理器上时并行性能下降。本文介绍了一种创建和删除数据副本（称为幻影副本）的并行算法，该算法可将邻域数据本地化以进行计算，同时最大程度地减少进程间的通信。该算法的主要特征是：（1）它可以根据选定的邻接关系在1D，2D或3D网格中创建任何允许的拓扑顺序的幻影副本。（2）它在重影创建过程中利用了邻域通信模式，从而消除了所有人之间的通信。（3）对于需要邻居邻居的应用程序，算法可以创建n个重影层数，直到可以划分整个分区网格的程度。对于IBM BG / P和Cray XE6体系结构，最多可提供32,768个处理器的核心扩展结果。当在并行超收敛补丁恢复误差估计器中使用该算法时，该算法还导致可伸缩的结果，该应用程序经常访问邻域数据以进行计算。