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The Virtual Environment for Sensor Performance Assessment (VESPA) project requires enormous, high-fidelity landscape models to generate synthetic sensor imagery with little to no artificial artifacts. These highfidelity landscapes require a memory footprint substantially larger than a single High Performance Computer’s (HPC) compute node’s local memory. Processing geometries this size requires distributing the geometry over multiple compute nodes instead of including a full copy in each compute node, the common approach in parallel modeling applications. To process these geometric models in parallel memory on a high-performance computing system, the Geometry Engine component of the VESPA project includes an architecture for partitioning the geometry spatially using Morton codes and MPI (Message Passing Interface) collective communication routines. The methods used for this partitioning process will be addressed in this report. Incorporating this distributed architecture into the Geometry Engine provides the capability to distribute and perform parallel ray casting on landscape geometries over a Terabyte in size. Test case timings demonstrate scalable speedups as the number of processes are increased on an HPC machine. DISCLAIMER: The contents of this report are not to be used for advertising, publication, or promotional purposes. Citation of trade names does not constitute an official endorsement or approval of the use of such commercial products. All product names and trademarks cited are the property of their respective owners. The findings of this report are not to be construed as an official Department of the Army position unless so designated by other authorized documents. DESTROY THIS REPORT WHEN NO LONGER NEEDED. DO NOT RETURN IT TO THE ORIGINATOR. ERDC/ITL SR-20-3 iii

Using Morton codes to partition faceted geometry : an architecture for terabyte-scale geometry models