The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Workshop: The 9th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD-9)
Authors: Max Faykus III, Jon Calhoun, and Melissa Smith (Clemson University)
Abstract: Optical Coherence Tomography (OCT) is a fast and nondestructive technology for bacterial biofilm imaging. However, OCT generates approximately 100 GB per flow cell, complicating storage and data sharing. Data reduction reduces data complications by reducing the overhead and amount of data transferred. This work leverages similarities between layers of OCT images to minimize data in order to improve compression. This paper evaluates 5 lossless and 2 lossy state-of-the-art compressors as well as 2 pre-processing techniques to reduce the OCT data. Reduction techniques are evaluated to determine which compressor has the most significant compression ratio while maintaining a strong bandwidth and minimal image distortion. Results show SZ with frame before pre-processing is able to achieve the highest CR of 204.6× on its higher error bounds. The maximum compression bandwidth SZ on higher error bounds is ∼ 41𝑀𝐵/𝑠, for decompression bandwidth, it is able to outperform ZFP achieving ∼ 67𝑀𝐵/𝑠.