SC17 Denver, CO

P15: Toward Decoupling the Selection of Compression Algorithms from Quality Constraints

Authors: Julian Kunkel (German Climate Computing Center), Anastasiia Novikova (University of Hamburg), Eugen Betke (German Climate Computing Center)

Abstract: With the Scientific Compression Library (SCIL), we are developing a meta-compressor that allows users to set various quantities that define the acceptable error and the expected performance behavior. The library then chooses 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 determining scientific ground characteristics of tolerable noise, from the task of determining an optimal compression strategy given target noise levels and constraints. Without changing applications, it allows these codes to utilize future algorithms once they are integrated into the library.
Award: Best Poster Finalist (BP): no

Poster: pdf
Two-page extended abstract: pdf

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