SPERR Compression

Term: 2020 - 2023

Funding source: NSF

Website: https://github.com/NCAR/SPERR

SPERR is a lossy compressor for scientific data (2D or 3D floating-point data, mostly produced by numerical simulations). SPERR produces excellent rate-distortion curves, meaning that it achieves the least amount of average error given a certain storage budget.

Under the hood, SPERR uses wavelet transforms, SPECK coding, and a custom outlier coding algorithm in its compression pipeline. This combination gives SPERR flexibility to compress targetting different quality controls, namely 1) bit-per-pixel (BPP), 2) peak signal-to-noise ratio (PSNR), and 3) point-wise error (PWE). The name of SPERR stands for SPeck with ERRor bounding.