Paper Info
Title
Optimizing Lossy Compression Rate-Distortion from Automatic Online Selection between SZ and ZFP.
Abstract
With ever-increasing volumes of scientific data produced by high-performance computing applications, significantly reducing data size is critical because of limited capacity of storage space and potential bottlenecks on I/O or networks in writing/reading or transferring data. SZ and ZFP are two leading BSD licensed open source C/C++ libraries for compressed floating-point arrays that support high throughput read and write random access. However, their performance is not consistent across different data sets and across different fields of some data sets, which raises the need for an automatic online (during compression) selection between SZ and ZFP, with minimal overhead. In this paper, the automatic selection optimizes the rate-distortion, an important statistical quality metric based on the signal-to-noise ratio. To optimize for rate-distortion, we investigate the principles of SZ and ZFP. We then propose an efficient online, low-overhead selection algorithm that predicts the compression quality accurately for two compressors in early processing stages and selects the best-fit compressor for each data field. We implement the selection algorithm into an open-source library, and we evaluate the effectiveness of our proposed solution against plain SZ and ZFP in a parallel environment with 1,024 cores. Evaluation results on three data sets representing about 100 fields show that our selection algorithm improves the compression ratio up to 70 percent with the same level of data distortion because of very accurate selection (around 99 percent) of the bestfit compressor, with little overhead (less than 7 percent in the experiments).
Year
DOI
Venue
2018
10.1109/tpds.2019.2894404
IEEE Transactions on Parallel and Distributed Systems
Keywords
Field
DocType
Compressors,Distortion,Rate-distortion,Data models,Measurement,Quantization (signal),Transforms
Data field,Data set,Lossy compression,Computer science,Selection algorithm,Algorithm,Real-time computing,Gas compressor,Compression ratio,Distortion,Fold (higher-order function)
Journal
Volume
Issue
ISSN
abs/1806.08901
8
1045-9219
Citations 
PageRank 
References 
7
0.47
31
Authors
5
Name
Order
Citations
PageRank
Dingwen Tao112917.66
Sheng Di273755.88
Xin Liang310712.74
Zizhong Chen492469.93
Franck Cappello53775251.47