This project has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No 654220. An award of computer time was provided by the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.

{"references": ["Axel Huebl, Ren\u00e9 Widera, Felix Schmitt, Alexander Matthes, Norbert Podhorszki, Jong Youl Choi, Scott Klasky, and Michael Bussmann (2017). On the Scalability of Data Reduction Techniques in Current and Upcoming HPC Systems from an Application Perspective, DOI:10.1007/978-3-319-67630-2_2"]}

Supplementary materials with all used benchmark scripts, plot scripts, benchmark results and PIConGPU example data for the submission to "The 1st International Workshop on Data Reduction for Big Scientific Data (DRBSD-1)" held in conjunction with ISC 2017 in Frankfurt, Germany.