Shin-Rong Tsai
Shin-Rong Tsai is a research scientist at the University of Illinois Urbana-Champaign School of Information Sciences. She has worked on developing astrophysics simulations, processing and visualizing extensive data, and improving application performance when scaling up in high-performance computing clusters. Her work now focuses on creating an in situ analysis tool that enables ongoing simulations to use Python to analyze data. She also develops tools for analyzing and visualizing volumetric data.
Sessions
In the era of exascale computing, storage and analysis of large scale data have become more important and difficult. We present libyt, an open source C++ library, that allows researchers to analyze and visualize data using yt or other Python packages in parallel during simulation runtime. We describe the methods for reading adaptive mesh refinement data structure, handling data transition between Python and simulation with minimal memory overhead, and conducting analysis with no additional time penalty using Python C API and NumPy C API. We demonstrate how it solves the problem in astrophysical simulations and increases disk usage efficiency.