The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Workshop: ISAV 2022: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization
Authors: Yoshiaki Yamaoka (Kobe University, Japan); Ken Iwata (Kobe University, Japan; RIKEN Center for Computational Science (R-CCS)); Naohisa Sakamoto (Kobe University, Japan); and Jorji Nonaka (RIKEN Center for Computational Science (R-CCS))
Abstract: Although in situ visualization can reduce the amount of data written to the storage, in situ visualization can still generate large amount of data for subsequent analysis. For instance, from different viewpoints at every visualization time step. Considering that some of these images can be similar, an appropriate image selection to reduce the total number of images would be beneficial to minimize the analysis time for understanding the underlying simulation phenomena without missing important features. As an approach for such smart in situ visualization, we have worked on adaptive time step selection for skipping time steps with small amount of change between time steps. In this lightning talk, focusing on the set of images which can be generated from different viewpoints at every time step, we will present a PSNR-based image selection approach for eliminating similar images to further reduce the total number of images, targeting smarter in situ visualization.