ParTransgrid: A scalable parallel preprocessing tool for unstructured‐grid cell‐centered computational fluid dynamics applications

Abstract

AbstractThe development of a basic scalable preprocessing tool is the key routine to accelerate the entire computational fluid dynamics (CFD) workflow toward the exascale computing era. In this work, a parallel preprocessing tool, called ParTransgrid, is developed to translate the general grid format like CFD General Notation System into an efficient distributed mesh data format for large‐scale parallel computing. Through ParTransgrid, a flexible face‐based parallel unstructured mesh data structure designed in Hierarchical Data Format can be obtained to support various cell‐centered unstructured CFD solvers. The whole parallel preprocessing operations include parallel grid I/O, parallel mesh partition, and parallel mesh migration, which are linked together to resolve the run‐time and memory consumption bottlenecks for increasingly large grid size problems. An inverted index search strategy combined with a multi‐master‐slave communication paradigm is proposed to improve the pairwise face matching efficiency and reduce the communication overhead when constructing the distributed sparse graph in the phase of parallel mesh partition. And we present a simplified owner update rule to fast the procedure of raw partition boundaries migration and the building of shared faces/nodes communication mapping list between new sub‐meshes with an order of magnitude of speed‐up. Experiment results reveal that ParTransgrid can be easily scaled to billion‐level grid CFD applications, the preparation time for parallel computing with hundreds of thousands of cores is reduced to a few minutes.