Resumen
Computational fluid dynamic simulations involve large state data, leading to performance degradation due to data transfer times, while requiring large disk space. To alleviate the situation, an adaptive lossy compression algorithm has been developed, which is based on regions of interest. This algorithm uses prediction-based compression and exploits the temporal coherence between subsequent simulation frames. The difference between the actual value and the predicted value is adaptively quantized and encoded. The adaptation is in line with user requirements, that consist of the acceptable inaccuracy, the regions of interest and the required compression throughput. The data compression algorithm was evaluated with simulation data obtained by the discontinuous Galerkin spectral element method. We analyzed the performance, compression ratio and inaccuracy introduced by the lossy compression algorithm. The post processing analysis shows high compression ratios, with reasonable quantization errors.