Register

Speaker: Alex Razoumov (SFU)

Abstract: As numerical simulations continue to grow in size and complexity, the I/O bottleneck makes it impossible to save all generated data for later analysis. In-situ techniques address this challenge by running analysis and visualization in real time, while the data are still in memory on the HPC system running the simulation, eliminating the need to write everything to disk. Several in-situ visualization frameworks exist, including ParaView's Catalyst, VisIt's LibSim, Ascent, and SENSEI.

In this hands-on workshop, we will focus on Catalyst2, which allows you to analyze and visualize your simulation data using familiar ParaView pipelines. Catalyst2 provides an API for describing and passing data arrays -- computational meshes and fields -- from your simulation to the library, which then converts these arrays into the appropriate VTK data structures. This happens without requiring the user to understand the underlying VTK data model and without duplicating data in memory. This framework is designed to scale to very large datasets and to thousands of CPU cores via MPI.

The goal of this workshop is to instrument a simple C code with the Catalyst2 library and produce in-situ outputs, including data extracts and rendered images, using ParaView's Python scripting.

Prerequisites: To participate in the hands-on exercises, please install ParaView on your computer. You can download it from the official website. Familiarity with ParaView basics -- creating a visualization pipeline, applying filters, and scripting -- is assumed and covered in earlier sessions. Some knowledge of C would be helpful, but we'll take things step by step.