Data Compression

📜 Data Compression

This paper surveys a variety of data compression methods spanning almost 40 years of research, from the work of Shannon, Fano and Huffman in the 40's, to a technique developed in 1986.

Scientific Data Compression

📜 Fast Error-bounded Lossy HPC Data Compression with SZ

This is the first version of SZ. In this paper, SZ is introduced to achieve data reduction using regression-based data point prediction.
📜 Significantly Improving Lossy Compression for Scientific Data Sets Based on Multidimensional Prediction and Error-Controlled Quantization

This work is known as SZ-1.4. In this work, SZ employs multi-dimensional data prediction so that data with dimension larger than 1 is no longer linearized into single dimension before compression. In this way, more data locality is preserved thus compression ratio is improved.
📜 Error-Controlled Lossy Compression Optimized for High Compression Ratios of Scientific Datasets

This work is known as SZ-2.0. In this work, authors proposed an online selection tool between 2 predictors, the mean-integrated Lorenzo predictor and linear regression-based predictor. Users can choose the predictor that yields larger compression ratio with higher prediction accuracy.
📜 Fixed-Rate Compressed Floating-Point Arrays
📜 FPC: A High-Speed Compressor for Double-Precision Floating-Point Data