In Situ Analysis and Visualization with ParaView Catalyst and Ascent

Scientific visualization and analysis are key ingredients in HPC simulation workflows. For decades, the dominant paradigm has been post-hoc visualization; simulation codes iterate and save files to disk, giving the domain scientists the opportunity to read the data back at a later time for analysis. In recent years though, this paradigm has been stressed by an ever-diverging rate of growth between I/O and compute speeds. In-situ processing helps mitigate these I/O bottlenecks, enabling simulation and visualization calculations to run in-memory, at higher spatial and temporal resolution, avoiding the transfer of raw data to disks. This tutorial introduces ParaView Catalyst and Ascent, two open-source implementations enabling in-situ processing. Both packages share a common project, called Conduit, which provides an intuitive model for describing hierarchical scientific data in C++, C, Fortran, and Python. We will cover how to describe simulation data with Conduit and how Ascent or Catalyst can transform data, render images, and export results, discussing the pros and cons of both implementations. We close the loop demonstrating how Ascent can also execute ParaView scripts. Attendees can follow along, execute some tutorial examples using Jupyter Notebooks, and deploy two example mini-apps (mesh- and particle-based) to illustrate the ideas presented.

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Contributors:

• Jean M. Favre (Swiss National Supercomputing Center)
• François Mazen (Kitware Europe)