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

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.

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