This paper presents a distributed memory method for anisotropic mesh adaptation that is designed to avoid the use of collective communication and global synchronization techniques. In the presented method, meshing functionality is separated from performance aspects by utilizing a separate entity for each - a multicore cc-NUMA-based (shared memory) mesh generation software and a parallel runtime system that is designed to help applications leverage the concurrency offered by emerging high-performance computing (HPC) architectures. First, an initial mesh is decomposed and its interface elements (subdomain boundaries) are adapted on a single multicore node (shared memory). Subdomains are then distributed among the nodes of an HPC cluster so that their interior elements are adapted while interface elements (already adapted) remain frozen to maintain mesh conformity. Lessons are presented regarding some re-designs of the shared memory software and how its speculative execution model is utilized by the distributed memory method to achieve good performance. The presented method is shown to generate meshes (of up to approximately 1 billion elements) with comparable quality and performance to existing state-of-the-art HPC meshing software.

翻译：本文提出了一种分布式内存的各向异性网格自适应方法，该方法旨在避免使用集体通信和全局同步技术。在所提出的方法中，网格生成功能与性能方面通过两个独立实体实现分离——一个基于多核cc-NUMA（共享内存）的网格生成软件，以及一个并行运行时系统，该系统旨在帮助应用程序利用新兴高性能计算（HPC）架构提供的并发性。首先，对初始网格进行分解，并在单个多核节点（共享内存）上对其界面单元（子域边界）进行自适应处理。随后将子域分配到HPC集群的各个节点中，使其内部单元得以自适应调整，而界面单元（已完成自适应）保持冻结状态以维持网格一致性。本文总结了共享内存软件的部分重新设计经验，并阐述了分布式内存方法如何利用其推测执行模型以实现良好性能。实验表明，该方法生成的网格（最高达约10亿单元）在质量和性能方面与现有最先进的HPC网格生成软件具有可比性。