Significantly Improving Lossy Compression for Scientific Data Sets Based on Multidimensional Prediction and Error-Controlled Quantization

Today's HPC applications are producing extremely large amounts of data, such that data storage and analysis are becoming more challenging for scientific research. In this work, we design a new error-controlled lossy compression algorithm for large-scale scientific data. Our key contribution is...

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Vydané v:	Proceedings - IEEE International Parallel and Distributed Processing Symposium s. 1129 - 1139
Hlavní autori:	Dingwen Tao, Sheng Di, Zizhong Chen, Cappello, Franck
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.05.2017
Predmet:	Adaptation models Compression algorithms Data models Encoding Measurement Predictive models Quantization (signal)
ISSN:	1530-2075
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