papers-we-love_papers-we-love/data_compression

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(SZ-0.1)

  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(SZ-1.4)

  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(SZ-2.0)

  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(ZFP)

• 📜 FPC: A High-Speed Compressor for Double-Precision Floating-Point Data