Code Examples

The examples directory includes ten programs that make use of the compressor.

Simple Compressor

The simple program is a minimal example that shows how to call the compressor and decompressor on a double-precision 3D array. Without the -d option, it will compress the array and write the compressed stream to standard output. With the -d option, it will instead read the compressed stream from standard input and decompress the array:

simple > compressed.zfp
simple -d < compressed.zfp

For a more elaborate use of the compressor, see the zfp utility.

Compressed-Array C++ Classes

The array program shows how to declare, write to, and read from zfp’s compressed-array C++ objects (in this case, 2D double-precision arrays), which is essentially as straightforward as working with STL vectors. This example initializes a 2D array with a linear ramp of 12 × 8 = 96 values using only four bits of storage per value, which using uncompressed storage would not be enough to distinguish more than 16 different values. For more advanced compressed-array features, see the tutorial.

Diffusion Solver

The diffusion example is a simple forward Euler solver for the heat equation on a 2D regular grid, and is intended to show how to declare and work with zfp’s compressed arrays, as well as give an idea of how changing the compression parameters and cache size affects the error in the solution and solution time. The usage is:

diffusion [options]
  -a <tolerance> : absolute error tolerance (requires -c)
  -b <blocks> : cache size in number of 4x4 blocks
  -c : use read-only arrays (needed for -a, -p, -R)
  -d : use double-precision tiled arrays
  -f : use single-precision tiled arrays
  -h : use half-precision tiled arrays
  -i : traverse arrays using iterators instead of integer indices
  -j : use OpenMP parallel execution (requires -r)
  -n <nx> <ny> : grid dimensions
  -p <precision> : precision in uncompressed bits/value (requires -c)
  -r <rate> : rate in compressed bits/value
  -R : reversible mode (requires -c)
  -t <nt> : number of time steps

Here rate specifies the exact number of compressed bits to store per double-precision floating-point value; nx and ny specify the grid size (default = 128 × 128); nt specifies the number of time steps to take (the default is to run until time t = 1); and blocks is the number of uncompressed blocks to cache (default = nx / 2). The -i option enables array traversal via iterators instead of indices.

The -j option enables OpenMP parallel execution, which makes use of both mutable and immutable private views for thread-safe array access. Note that this example has not been optimized for parallel performance, but rather serves to show how to work with zfp’s compressed arrays in a multithreaded setting.

This example also illustrates how read-only arrays (-c) may be used in conjunction with fixed-rate (-r), fixed-precision (-p), fixed-accuracy (-a), or reversible (-R) mode.

The output lists for each time step the current rate of the state array and in parentheses any additional storage, e.g., for the block cache and index data structures, both in bits per array element. Running diffusion with the following arguments:

diffusion -r 8
diffusion -r 12
diffusion -r 16
diffusion -r 24

should result in this final output:

sum=0.995170 error=4.044954e-07
sum=0.998151 error=1.237837e-07
sum=0.998345 error=1.212734e-07
sum=0.998346 error=1.212716e-07
sum=0.998346 error=1.212716e-07

For speed and quality comparison, the solver solves the same problem using uncompressed double-precision row-major arrays when compression parameters are omitted. If one of -h, -f, -d is specified, uncompressed tiled arrays are used. These arrays are based on the zfp array classes but make use of the generic codec, which stores blocks as uncompressed scalars of the specified type (half, float, or double) while utilizing a double-precision block cache (like zfp’s compressed arrays).

The diffusionC program is the same example written entirely in C using the cfp wrappers around the C++ compressed array classes.

Speed Benchmark

The speed program takes two optional parameters:

speed [rate] [blocks]

It measures the throughput of compression and decompression of 3D double-precision data (in megabytes of uncompressed data per second). By default, a rate of 1 bit/value and two million blocks are processed.

PGM Image Compression

The pgm program illustrates how zfp can be used to compress grayscale images in the pgm format. The usage is:

pgm <param> <input.pgm >output.pgm

If param is positive, it is interpreted as the rate in bits per pixel, which ensures that each block of 4 × 4 pixels is compressed to a fixed number of bits, as in texture compression codecs. If param is negative, then fixed-precision mode is used with precision -param, which tends to give higher quality for the same rate. This use of zfp is not intended to compete with existing texture and image compression formats, but exists merely to demonstrate how to compress 8-bit integer data with zfp. See FAQs #20 and #21 for information on the effects of setting the precision.

PPM Image Compression

The ppm program is analogous to the pgm example, but has been designed for compressing color images in the ppm format. Rather than compressing RGB channels independently, ppm exploits common strategies for color image compression such as color channel decorrelation and chroma subsampling.

The usage is essentially the same as for pgm:

ppm <param> <input.ppm >output.ppm

where a positive param specifies the rate in bits per pixel; when negative, it specifies the precision (number of bit planes to encode) in fixed-precision mode.

In-place Compression

The inplace example shows how one might use zfp to perform in-place compression and decompression when memory is at a premium. Here the floating-point array is overwritten with compressed data, which is later decompressed back in place. This example also shows how to make use of some of the low-level features of zfp, such as its low-level, block-based compression API and bit stream functions that perform seeks on the bit stream. The program takes one optional argument:

inplace [tolerance]

which specifies the fixed-accuracy absolute tolerance to use during compression. Please see FAQ #19 for more on the limitations of in-place compression.


The iterator example illustrates how to use zfp’s compressed-array iterators and pointers for traversing arrays. For instance, it gives an example of sorting a 1D compressed array using std::sort(). This example takes no command-line options.

The iteratorC example illustrates the equivalent cfp iterator operations. It closely follows the usage shown in the iterator example with some minor differences. It likewise takes no command-line options.