Publication Date
4-2024
School
School of Business
Major
Computer Science
Keywords
image compression, quadtree, CUDA, MPI, parallelization, Python
Disciplines
Computer Sciences | Other Computer Sciences
Recommended Citation
Jones, Aidan, "Parallelized Quadtrees for Image Compression in CUDA and MPI" (2024). Senior Honors Theses. 1358.
https://digitalcommons.liberty.edu/honors/1358
Abstract
Quadtrees are a data structure that lend themselves well to image compression due to their ability to recursively decompose 2-dimensional space. Image compression algorithms that use quadtrees should be simple to parallelize; however, current image compression algorithms that use quadtrees rarely use parallel algorithms. An existing program to compress images using quadtrees was upgraded to use GPU acceleration with CUDA but experienced an average slowdown by a factor of 18 to 42. Another parallelization attempt utilized MPI to process contiguous chunks of an image in parallel and experienced an average speedup by a factor of 1.5 to 3.7 compared to the unmodified program.