The RCC-CFD VM Image is built using the open-source RCC-Apps image baking repository. If you’d like to deploy RCC-CFD using Terraform, see the Deploy with Terraform documentation. If you’d like to deploy RCC-CFD from the Google Cloud Marketplace, see the Deploy from Marketplace documentation. #Paraview cluster how to#How to add OpenFOAM to an existing clusterīasics of connecting Paraview Server on the RCC to your local Paraview client What is included in the RCC-CFD VM Images Alternatively, if you want to get started with a click-to-deploy solution that has OpenFOAM, Paraview, and GMSH installed, you can use the RCC-CFD Marketplace solution. The Research Computing Cluster (RCC) offers OpenFOAM and Paraview through virtual machine images that can be easily incorporated into an existing RCC. Paraview is an open-source toolkit for visualizing scientific data and is capable of leveraging clusters of compute instances for rendering large datasets. Please note that the short clips shared in the webinar were not recorded smoothly by Zoom, so it is best to watch these animations inside the presentations linked from the Contest website.OpenFOAM is an open-source finite-volume based computational fluid dynamics toolkit for simulating a variety of fluid phenomena. In this webinar we talked about some of the ideas suggested in the submissions. We saw many good submissions and a ton of innovative visualization ideas. The Contest challenge was to identify various flow features and visualize them clearly as they evolve in time. The simulation was conducted using Compute Canada’s Niagara cluster. This Contest dataset was a numerical simulation of convection in the Earth’s mantle containing 251 timesteps covering 500 Myr of geological time, data courtesy of the Pysklywec Lab (Russell Pysklywec and Hosein Shahnas) at the University of Toronto. The 2021 SciVis Contest organized jointly by IEEE and Compute Canada wrapped up on October 28th, with the official announcement of awards at the IEEE Vis conference. “Highlights from the 2021 SciVis Contest” Even though I demo Catalyst2 with C codes, it can be used from C, C++, Fortran, Python, and has also been demonstrated to work well with Julia simulation codes. This lets you interactively explore large datasets in memory without having to write them to disk. I also demo ParaView Live connecting from the ParaView GUI to a live simulation to modify an existing visualization pipeline while the simulation is running. These Catalyst Python scripts in turn can be easily generated with Extractors which have been part of ParaView since version 5.9. #Paraview cluster code#I show examples of instrumenting a C simulation code with Catalyst2 and applying various Catalyst Python scripts to generate data and images on the fly while the simulation is running. Catalyst2 framework can scale to very large datasets and thousands of CPU cores via MPI. Catalyst2 provides an API for describing and passing data arrays - computational meshes and fields - from your simulation to the Catalyst2 library which in turn converts these arrays into appropriate VTK data objects, without you having to know the VTK data model (unlike with the original Catalyst), and without duplicating these data arrays in memory. In this webinar I focus on Catalyst2 which is a significant rewrite of the original Catalyst framework. “In-situ visualization with ParaView Catalyst2”Ĭatalyst lets you perform analysis and visualization of your simulation data while your simulation is running, using familiar ParaView visualization pipelines. “3D graphs with NetworkX, VTK, and ParaView”.“Scripting and other advanced topics in VisIt visualization”.“Using ParaViewWeb for 3D Visualization and Data Analysis in a Web Browser”.“Data Visualization on Compute Canada’s Supercomputers”.“Novel Visualization Techniques from the 2017 Visualize This Challenge”.“Scientific visualization with Plotly”.“Using YT for analysis and visualization of volumetric data”.“Batch visualization on Compute Canada clusters”.“Photorealistic rendering with ParaView and OSPRay”.“Web-based 3D scientific visualization”.“Intermediate VMD topics: trajectories, movies, scripting”.“Workflows with Programmable Filter / Source in ParaView”.“Scientific visualization on NVIDIA GPUs”.“Remote visualization on Compute Canada clusters”.“Highlights from the 2021 SciVis Contest”.Table of Contents: “In-situ visualization with ParaView Catalyst2” “3D visualization for the humanities” slides (82 pages, last updated June 2022).VisIt full-day workshop slides (129 pages, last updated May 2017).ParaView full-day workshop slides (127 pages, last updated July 2022). #Paraview cluster full#For full documentation, please check the Visualization section in Compute Canada’s technical wiki.
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