Our zfp compressor for floating-point and integer data often achieves compression ratios on the order of 100:1, i.e., to less than 1 bit per value of compressed storage. zfp frequently gives more accurate results than competing compressors including our own fpzip. zfp Compression Ratio and Quality Rate-Distortion Comparisons zfp is a very fast compressor and decompressor for floating-point data that achieves up to 2 gigabytes/second throughput. zfp_write_header and zfp_field_metadata now fail if array dimensions are too large to fit in header. zfp 0.5.4—October 1, 2018 Added support for CUDA fixed-rate compression and decompression. Reversible Mode¶ As of zfp 0.5.5, reversible lossless compression is supported. As with the other compression modes, each block is compressed and decompressed independently, but reversible mode uses a different compression algorithm that ensures a bit-for-bit identical reconstruction of integer and floating-point data. This section describes the Intel® Integrated Performance Primitives data compression functions that implement the ZFP compressed data format. You can use the ZFP algorithm to perform lossy compression of 3D floating point data. The ZFP format and algorithm are described in [ZFP].

In spite of zfp using the least storage among all methods, its divergence field exhibits no artifacts and is visually identical to the uncompressed field. divergence[1].png Higher-order derivatives tend to be even more sensitive to compression-induced errors. zfp Arrays: Inline Compression zfp partitions d -dimensional arrays into small blocks of 4 d values, and these blocks are compressed or decompressed on demand as array accesses are made. Such compression on demand is often referred to as inline compression. The compression scheme implemented in this version of zfp has evolved from the method described in the paper cited above, and can conceptually be thought of as consisting of eight sequential steps in practice some steps are consolidated or exist only for illustrative purposes: 1 The d-dimensional array is partitioned into blocks of. A registered ZFP compression plugin for HDF5. Contribute to HDFGroup/H5Z-ZFP development by creating an account on GitHub.

05/05/2019 · zfp uses lossy but optionally error-bounded compression to achieve high compression ratios. Bit-for-bit lossless compression is also possible through one of zfp's compression modes. zfp works best for 2D, 3D, and 4D arrays that exhibit spatial correlation, such as continuous fields from physics simulations, natural images, regularly sampled terrain surfaces, etc. zfp compression of 1D. This project supports the development of zfp, which provides a compressed multidimensional array primitive for floating-point and integer data that supports very high-speed read and write random access. zfp’s tiled arrays allow the user to specify exactly how much storage to use on a per array or even per tile basis. In addition to meeting storage constraints, zfp provides controls for.

Lossy Compression¶ The zfp lossy compression scheme is based on the idea of breaking a d-dimensional array into independent blocks of 4 d values each, e.g., 4 × 4 × 4 values in three dimensions. Each block is compressed/decompressed entirely independently from all other blocks. In this sense, zfp is similar to current hardware texture.

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