Fast and effective lossy compression algorithms for scientific datasets

Jeremy Iverson, Chandrika Kamath, George Karypis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

41 Scopus citations

Abstract

This paper focuses on developing effective and efficient algorithms for compressing scientific simulation data computed on structured and unstructured grids. A paradigm for lossy compression of this data is proposed in which the data computed on the grid is modeled as a graph, which gets decomposed into sets of vertices which satisfy a user defined error constraint ε. Each set of vertices is replaced by a constant value with reconstruction error bounded by ε. A comprehensive set of experiments is conducted by comparing these algorithms and other state-of-the-art scientific data compression methods. Over our benchmark suite, our methods obtained compression of 1% of the original size with average PSNR of 43.00 and 3% of the original size with average PSNR of 63.30. In addition, our schemes outperform other state-of-the-art lossy compression approaches and require on the average 25% of the space required by them for similar or better PSNR levels.

Original languageEnglish (US)
Title of host publicationParallel Processing - 18th International Conference, Euro-Par 2012, Proceedings
Pages843-856
Number of pages14
DOIs
StatePublished - Oct 24 2012
Event18th International Conference on Parallel Processing, Euro-Par 2012 - Rhodes Island, Greece
Duration: Aug 27 2012Aug 31 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7484 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other18th International Conference on Parallel Processing, Euro-Par 2012
CountryGreece
CityRhodes Island
Period8/27/128/31/12

Fingerprint Dive into the research topics of 'Fast and effective lossy compression algorithms for scientific datasets'. Together they form a unique fingerprint.

Cite this