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Tag: Geometrical models
  • PUBLICATION NOTICE: Parallel File I/O for Geometric Models: Formats and Methods

    Abstract: Processing large amounts of data in a High-Performance Computing (HPC) environment can be throttled quickly without an efficient method for utilizing disk I/O. The Geometry Engine component of the Virtual Environment for Sensor Performance Assessment (VESPA) uses MPI-IO to load the geometric data in parallel and avoid creating a bottleneck on disk I/O interactions. This parallel I/O method requires formatting the data into specific binary file formats so each MPI process of the parallel program can determine where to read or write data without colliding with other MPI processes. Addressing the collision problem resulted in the development of two binary file formats, the Mesh Binary file (.mb) and the Scene Chunk Pack file (.scp). The Mesh Binary file contains the essential data required to recreate the landscape and vegetation geometry used by the Geometry Engine. The Scene Chunk Pack file is used to write the partitioned geometry to disk, so the ray casting engine can reload the distributed geometry without repeating the partitioning process. Both of these files together support reading and writing for the partitioning phase and the ray casting phase of the Geometry Engine. This report discusses these formats in detail and outlines how the Geometry Engine reads and writes these files in parallel on HPC.
  • PUBLICATION NOTICE: Using Morton Codes to Partition Faceted Geometry: An Architecture for Terabyte-Scale Geometry Models

    Abstract: 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 high-fidelity 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.