"An efficient distributed mesh data structure is needed to support
parallel adaptive analysis since it strongly influences the overall
performance of adaptive mesh-based simulations. In addition to the
general mesh-based operations, such as mesh entity creation/deletion,
adjacency and geometric classification, iterators, arbitrary attachable
data to mesh entities, etc., the distributed mesh data structure must
support (i) efficient communication between entities duplicated over
multiple processors, (ii) migration of mesh entities between processors,
and (iii) dynamic load balancing.
Issues associated with supporting parallel adaptive analysis on
unstructured meshes include dynamic mesh load balancing techniques, and
data structure and algorithms for parallel mesh adaptation.
The Parallel Unstructured Mesh Infrastructure (PUMI) is an unstructured,
distributed mesh data management system that is capable of handling
general non-manifold models and effectively supporting automated
adaptive analysis. PUMI supports a full range of operations on
unstructured meshes on massively parallel computers consisiting of five
libraries:
PCU - https://scorec.rpi.edu/pcu/
GMI - https://scorec.rpi.edu/pumi/pumi_geom.php
MDS - https://scorec.rpi.edu/~dibanez/core/mds.html
APF Mesh - https://scorec.rpi.edu/~dibanez/core/apfMesh_8h.html
APF Field - https://scorec.rpi.edu/apf/
https://scorec.rpi.edu/pumi/
https://scorec.rpi.edu/software.php
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