Toward highly parallel loading of unstructured meshes. (April 2022) - Meca, Ondřej; Říha, Lubomír; Jansík, Branislav; Brzobohatý, Tomáš
Highlights: Workow for highly-parallel loading of arbitrary mesh databases. The algorithm with provable linear speedup for large datasets. Reconstruction of a mesh with hundreds millions elements in several seconds. Independence from any particular data arrangement and data duplication within a database. Negligible run-time diffrences for arbitrary unstructured mesh databases. Abstract: This paper presents an algorithm for highly-parallel loading and processing of unstructured mesh databases in a distributed memory environment of large HPC clusters without collecting data into a single process. The algorithm is proved effective, having linear speedup in the large dataset limit. Demonstrated on Ansys CDB, EnSight, VTK Legacy, and XDMF databases, we show that it is possible to efficiently reconstruct meshes with 800 million nodes and 500 million elements in several seconds on thousands of processors, even from databases that were not designed to be read in parallel. The algorithm is implemented in our MESIO library that can be used as (i) an efficient parallel loader (e.g. for numerical physical solvers) or as (ii) a high performing parallel converter between mesh databases.