Data compression for high-performance computational fluid dynamics

Date(s) : 14/12/2018
14 h 00 min - 15 h 00 min

High-performance computing can produce large volumes of output data. A computational fluid dynamics simulation using several hundred or thousands of processor cores would allocate three-dimensional fields of many Gigabytes per hydrodynamic variable. Even though data reduction may be performed during the course of computation in order to only store the quantities of interest including hydrodynamic forces, etc., it is often necessary to store full three-dimensional fields for purposes such as simulation restart, time-resolved flow visualization or exploratory analyses. In this talk, I will present a wavelet-based method for compression of fluid flow simulation data. It is inspired by image compression, and it consists of discrete wavelet transform, quantization adapted for floating-point data, and entropy coding. I will discuss different aspects of these numerical methods, open-source software implementation and show example numerical tests, ranging from idealized configurations to realistic global weather simulation data.

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