Director of Research (if dissertation) or Advisor (if thesis)
Lumetta, Steven Sam
Butala, Mark
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Gpu Acceleration
Solar Tomography
Language
eng
Abstract
Tomography reconstructs cross-sectional images from multi-directional data and plays a crucial role in fields such as medical imaging and solar physics. In solar physics, tomography is crucial for reconstructing 3-D electron density volumes of the solar corona from 2-D coronagraph images. This thesis investigates how factors like grid resolution, the number of viewpoints, and view angles influence reconstruction accuracy and computational cost in solar tomography. Through a series of controlled experiments using synthetic data, we explore the tradeoffs between these factors to provide insights into optimizing future solar tomography tasks. To enable these computationally intensive experiments, we develop a GPU-accelerated forward model framework specifically designed for spherical grids. This framework achieves a significant speedup of 27x to 270x compared to sequential implementations, allowing us to conduct large-scale simulations and reconstructions efficiently. This work not only advances the understanding of the solar tomography reconstruction but also paves the way for future advancements in space tasks.
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