Adaptive mesh refinement (AMR) algorithms require efficient structures to store and operate upon volumetric grid data that will be used to distribute work among processes. When inefficient algorithms are used, AMR-enabled software may have its scaling negatively impacted as processes are starved for work. We present a variable-resolution octree-based structure which efficiently handles the set operations needed for AMR operations such as calculating process communication schedules and buffer zones. Results indicate a marked improvement in execution times when large amounts of volumetric data are processed, at the price of a structure creation and traversal penalty for smaller amounts of data. The BL-octree (“blocktree”) data structure presented in this paper will therefore be of use in massively parallel AMR environments, where the cost of distributing AMR workloads across many tens of thousands or more processes can be reduced.
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