Z-checker: A Framework for Assessing Lossy Compression of Scientific Data

TL;DR

Z-checker is an open-source framework that systematically evaluates lossy compression quality of scientific data, aiding developers and users in understanding data alterations and selecting optimal compression strategies.

Contribution

It introduces the first comprehensive, modular tool for assessing lossy scientific data compression, integrating analysis, visualization, and evaluation metrics.

Findings

Provides detailed data quality analysis post-compression

Enables comparison of different lossy compressors on datasets

Supports adaptive, fine-grained evaluation of compression effects

Abstract

Because of vast volume of data being produced by today's scientific simulations and experiments, lossy data compressor allowing user-controlled loss of accuracy during the compression is a relevant solution for significantly reducing the data size. However, lossy compressor developers and users are missing a tool to explore the features of scientific datasets and understand the data alteration after compression in a systematic and reliable way. To address this gap, we have designed and implemented a generic framework called Z-checker. On the one hand, Z-checker combines a battery of data analysis components for data compression. On the other hand, Z-checker is implemented as an open-source community tool to which users and developers can contribute and add new analysis components based on their additional analysis demands. In this paper, we present a survey of existing lossy compressors. Then we describe the design framework of Z-checker, in which we integrated evaluation metrics proposed in prior work as well as other analysis tools. Specifically, for lossy compressor developers, Z-checker can be used to characterize critical properties of any dataset to improve compression strategies. For lossy compression users, Z-checker can detect the compression quality, provide various global distortion analysis comparing the original data with the decompressed data and statistical analysis of the compression error. Z-checker can perform the analysis with either coarse granularity or fine granularity, such that the users and developers can select the best-fit, adaptive compressors for different parts of the dataset. Z-checker features a visualization interface displaying all analysis results in addition to some basic views of the datasets such as time series. To the best of our knowledge, Z-checker is the first tool designed to assess lossy compression comprehensively for scientific datasets.