Scientific Compression Library

The Scientific Compression Library (SCIL) is a meta-compressor that decouples definition of user requirements from the selection of the compression algorithm. In detail, it allows users to set various quantities that define the acceptable error and the expected performance behavior. The library then aims to choose the appropriate chain of algorithms to yield the users requirements. This approach is a crucial step towards a scientifically safe use of much-needed lossy data compression, because it disentangles the tasks of identifying tolerable error bounds and performance behavior from the selection and configuration of the algorithms.

Contact Dr. Julian Kunkel
Repository Public on GitHub
URL Also developed in the project: AIMES