Parallel Implementation of an Oil Reservoir Data Visualization Tool

Abstract

This thesis proposes five parallel-algorithms for 3D oil reservoir-data visualization-tool. The proposed algorithms depend on shared, distributed and hybrid memory-models and it can be used as general-parallel algorithms for other-applications. The suggested parallel-implementations are tested by different data sizes using two-real platforms, ERI-HPC and Virtual-Cluster on ERI-OpenStack cloud. This thesis provides five-contributions. First, developing-scalable and reusable-parallel algorithms for 3D oil-reservoir data visualization-tool which depend on shared, distributed and hybrid memory-models. Second, testing-the parallel-implementations on-traditional HPC-system. Third, building Virtual-Cluster on OpenStack-Cloud as a virtual-system and elaborate the network-traffic between virtual-machines. Fourth, studying-the performance-of parallel 3D oil-reservoir data-visualization-tool on the Virtual Cluster. Finally, comparing the performance of parallel-oil reservoir data visualization-tool on HPC-system and virtual cluster.