Huge data advent in high-performance computing (HPC) applications such as fluid flow simulations usually hinders the interactive processing and exploration of simulation results. Such an interactive data exploration not only allows scientiest to 'play' with their data but also to visualise huge (distributed) data sets in both an efficient and easy way. Therefore, we propose an HPC data exploration service based on a sliding window concept, that enables researches to access remote data (available on a supercomputer or cluster) during simulation runtime without exceeding any bandwidth limitations between the HPC back-end and the user front-end.
@article{arxiv.1807.00149,
title = {Interactive data exploration for high-performance fluid flow computations through porous media},
author = {Nevena Perović and Jérôme Frisch and Ralf-Peter Mundani and Ernst Rank},
journal= {arXiv preprint arXiv:1807.00149},
year = {2018}
}