This is an idea proposed in 2023 as a Cambrige Computer Science Part III or MPhil project, and has been completed by Omar Tanner. It was supervised by Anil Madhavapeddy and Sadiq Jaffer as part of my Planetary Computing project.
Geospatial data processing can benefit from by applying lightweight compression techniques to data in GeoTIFF format, addressing the challenge of modern CPU bandwidth surpassing RAM bandwidths. This project will explore how to mitigate the impact of poor cache locality and the resulting memory bottlenecks by leveraging CPU superscalar capabilities and SIMD instructions. By implementing SIMD-optimised compression, data can remain compressed in RAM and closer to the CPU caches, facilitating faster access and alleviating memory constraints.