SZ is a modular parametrizable lossy compressor framework for scientific data
(floating point and integers). It has applications in simulations, AI and
instruments. It is a production quality software and a research platform for
lossy compression. SZ is open and transparent. Open because all interested
researchers and students can study or contribute to it. Transparent because all
performance improvements are detailed in publications.

SZ can be used for classic use-cases: visualization, accelerating I/O, reducing
memory and storage footprint and more advanced use-cases like compression of DNN
models and training sets, acceleration of computation, checkpoint/restart,
reducing streaming intensity and running efficiently large problems that cannot
fit in memory. Other use-cases will augment this list as users find new
opportunities to benefit from lossy compression of scientific data.

SZ has implementations on CPU, GPU, and FPGA and is integrated in the main I/O
libraries: HFD5, ADIOS, PnetCDF.
