Timbwaoga Aime Judicael Ouermi (TAJO) is a Ph.D. student at the University of Utah. He is currently co-advised by Dr. Martin Berzins and Dr. Mike Kirby. Before joining the University of Utah, TAJO obtained his bachelor's degree in Computer Science and Physics at the University of Oregon. While at the University of Oregon, he worked in the Computing and Data Understanding at eXtreme Scale (CDUX) research group exploring particle path tracing under Lagrangian representation. He was advised by Dr. Hank Child.
This project focuses on investigating numerical projection methods that preserve accuracy and physical properties such as mass conservation and positivity. For instance a negative density and may cause a numerical scheme to blow up.
This project focuses on performance optimization of Numerical Weather Prediction codes for current and potential future architectures. As we move to the next generation of supercomputer with complex integrated architectures, it is important to develop modify codes to take advantage of the hardware resources while maintaining portability. In this work we investigate programing paradigms for portability, and advance optimization strategies for high performing and portable NWP codes.
In this project we investigated different search structures for Lagrangian based particle path tracing. This work particularly investigated regular and bounding volume hierarchy(BVH) based tree structures. The results from the studies can be found here.[pdf]
In this project, we developed a built a Monte Carlo Radiative Transfer (MRT) code. This project is built on the framework of taking random walks and computing different properties of each photon at each step.