Fast Topology-Aware Lossy Data Compression with Full Preservation of Critical Points and Local Order

TL;DR

This paper introduces a fast, topology-aware lossy data compressor that fully preserves local order and critical points, outperforming existing methods in speed and compression ratio.

Contribution

It presents the first compressor that preserves full local order and critical points while being significantly faster than previous topology-preserving algorithms.

Findings

Runs orders of magnitude faster than prior topology-preserving compressors.

Achieves higher compression ratios than lossless methods.

Produces bit-for-bit identical output on CPUs and GPUs.

Abstract

Many scientific codes and instruments generate large amounts of floating-point data at high rates that must be compressed before they can be stored. Typically, only lossy compression algorithms deliver high-enough compression ratios. However, many of them provide only point-wise error bounds and do not preserve topological aspects of the data such as the relative magnitude of neighboring points. Even topology-preserving compressors tend to merely preserve some critical points and are generally slow. Our Local-Order-Preserving Compressor is the first to preserve the full local order (and thus all critical points), runs orders of magnitude faster than prior topology-preserving compressors, yields higher compression ratios than lossless compressors, and produces bit-for-bit the same output on CPUs and GPUs.