DevOps for Catalyst In Situ Visualization and Analysis at Sandia National Laboratories
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Proceedings of ISAV 2022: IEEE/ACM International Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis
This paper reports on Catalyst usability and initial adoption by SPARC analysts. The use case approach highlights the analysts' perspective. Impediments to adoption can be due to deficiencies in software capabilities, or analysts may identify mundane inconveniences and barriers that prevent them from fully leveraging Catalyst. With that said, for many analyst tasks Catalyst provides enough relative advantage that they have begun applying it in their production work, and they recognize the potential for it to solve problems they currently struggle with. The findings in this report include specific issues and minor bugs in ParaView Python scripting, which are viewed as having straightforward solutions, as well as a broader adoption analysis.
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A new in transit Data Service is presented and compared to the traditional file-based workflow and the newly refactored in situ Catalyst workflow. Each workflow is enabled by the IOSS mesh interface equipped with data management layers for Exodus and CGNS (file-based), Catalyst (in situ), and FAODEL (in transit). FAODEL is a distributed object store that can transmit data across MPI allocations. Catalyst is a Para View-based visualization capability developed as part of the CSSE Data Services effort. The workflows considered here take SPARC data into Catalyst for visualization post-processing. Although still in unoptimized form, we show that the in transit approach is a viable alternative to file-based and in situ workflows and offers several advantages to both simulation and post-processing developers. Since IOSS is a mature interface with wide adoption across Sandia and externally, each workflow can be reconfigured to use different simulations that generate mesh data and post-processing tools that consume it.
ACM International Conference Proceeding Series
The Sandia National Laboratories (SNL) Large-Scale Computing Initiative (LSCI) milestone required running two parallel simulation codes at scale on the Trinity supercomputer at Los Alamos National Laboratory (LANL) to obtain presentation quality visualization results via in-situ methods. The two simulation codes used were Sandia Parallel Aerosciences Research Code (SPARC) and Nalu, both fluid dynamics codes developed at SNL. The codes were integrated with the ParaView Catalyst in-situ visualization library via the SNL developed Input Output SubSystem (IOSS). The LSCI milestone had a relatively short time-scale for completion of two months. During setup and execution of in-situ visualization for the milestone, there were several challenging issues in the areas of software builds, parallel startup-times, and in the a priori specification of visualizations. This paper will discuss the milestone activities and technical challenges encountered in its completion.
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34th Thermophysics Conference
This paper presents an investigation of a technique for using two-dimensional bodies composed of simple polygons with a body-decoupled uniform Cartesian grid in the Direct Simulation Monte Carlo method (DSMC). The method employs an automated grid preprocessing scheme beginning from a CAD geometry definition file, and is based on polygon triangulation using a trapezoid algorithm. A particle-body intersection time comparison is presented between the Icarus DSMC code using a body-fitted structured grid, and using a structured body-decoupled Cartesian grid with both linear and logarithmic search techniques. A comparison of neutral flow over a cylinder is presented using the structured body fitted grid, and the Cartesian body de-coupled grid.