Intelligent Light and FieldView

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ISC Workshop on In Situ Visualization

Time step from the evolution of temporal mixing layer from initial to vortex breakdown. AVF/Leslie simulation performed using up to 131,072 cores on DOE's TITAN supercomputer. In situ processing using VisIt software delivered the images related plots and XDB files for the researchers. Time step 150,000 out of 200,000.

This summer I presented a talk called In Situ Production of Extract Databases for Visualization to the Workshop on In Situ Visualization at the ISC Conference held in Frankfurt, Germany. In situ takes workflows that have been created post hoc and executes them directly on simulation data in memory while the simulation is running. The workshop was attended by visualization experts mainly from Europe and the US and talks focused on using in situ software to address the challenges of being able to save sufficient simulation data on supercomputers.

Hank Childs from the University of Oregon, a prominent visualization expert, gave a keynote address emphasizing the importance of in situ against the backdrop of upcoming exascale machines with their diminishing memory per core and lower relative I/O bandwidth compared to today's machines. Jens Henrik Goebbert from Aachen University presented an abstraction library that simplifies in situ integration with multiple in situ infrastructures, including Libsim. Roberto Sisneros from NCSA presented work on a parameter study highlighting the importance of providing good default application settings and showed that performance for VisIt's streamline plot could be enhanced by simply improving the default settings.

My talk summarized Intelligent Light's in situ efforts with VisIt, Libsim and our extract database files (XDB). Specifically, we instrument a simulation for in situ using Libsim, which brings VisIt's capabilities into the simulation. We developed a library that efficiently writes the FieldView XDB files and added it as an export option to VisIt. The simulation uses VisIt to create surface geometry extracts, typically without making any copies of simulation data, and exports the extract as a FieldView XDB file. Tight coupling of simulation to visualization and analysis provides opportunities to perform data reductions that result in smaller, concentrated, more useful results being written out more frequently, avoiding the costs of writing and later reading large volume datasets.

​I presented results from running the AVF-LESLIE combustion code on the Titan machine at Oak Ridge National Laboratory using an in situ rendering workflow and our extract database workflow. For the rendering workflow we were able to run the code up to 131K cores and render images of slices and isosurfaces from the simulation every 5 time steps to produce a visualization of a turbulent mixing layer of 2 fluids. In another of our experiments, we extracted surface-based results, saving the geometry plus field data to our XDB format for later post-processing within FieldView. We saved XDB extracts from every 5th time step, taking around 2% of the simulation runtime. Each XDB file was over 200x smaller than the corresponding volume data file. We wrote 20 XDB files for every volume output file and the combined size of 20 XDB files was still 10x smaller than a single volume output file.

This work is supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research under Award Number DE-SC0012449.

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Libsim Improvements to Enable Better In Situ Workflows

This year’s Department of Energy Computer Graphics Forum meeting in Pacific Grove, CA, brought together leading visualization experts from the DOE and DOD to share their experiences developing state of the art software needed to analyze results from future exascale computers. The meeting consisted mainly of invited talks spanning a broad set of topics, including: advances in display wall technology, vendor libraries that maximize performance using hardware, software updates, realistic rendering and in situ analysis.

In my talk, “Libsim Improvements to Enable Better In Situ Workflows”, I outlined the significant reductions in both data size and time spent processing the data that can be realized by extracting surfaces of interest and saving data to the XDB format. These XDB files can then be read into FieldView or XDBview.

Additional performance benefits of this workflow are gained due to the fact that subsequent post-processing does not involve reading large amounts of volume-based results. The performance benefits are magnified when the workflow is applied in situ because the data extraction can be done while data are in the solver memory as opposed to being done after writing volume data to disk. In situ workflow sidesteps the I/O bottleneck associated with writing (and later reading) large amounts of data since it restricts data to only the features of interest, which are a small subset of the original data.

My talk demonstrated Intelligent Light’s commitment to in situ and highlighted the improvements that we have made to Libsim, the VisIt in situ library, that enable it to scale to over 131K cores using the AVF-LESLIE combustion code on the Titan supercomputer at Oak Ridge National Laboratory. We have made numerous enhancements to Libsim that improve its efficiency and ability to seamlessly accept data from the host solver code. For instance, we made enhancements that permit zero-copy passing of data from the solver to Libsim when data are not organized contiguously in memory. In addition, we eliminated several bottlenecks that affected VisIt’s rendering and scaling performance on the Titan machine. We also streamlined the creation of XDB files by developing a prototype parallel XDB library based on Oak Ridge’s high performance ADIOS framework. Taken together, these improvements to Libsim and VisIt set the stage for even larger in situ runs to come and eliminate many barriers to using in situ and an extract-based workflow.

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Leading the Way With In Situ Extracts

At Intelligent Light, we continue to lead the charge for the adoption of in situ, a technique that can maximize insight from simulation runs while also avoiding the problems caused by saving, storing and moving massive amounts of data. Our work this year shows that using in situ allows the CFD practitioner to increase resolution by saving data at a higher frequency, while still saving far less data overall. This reduces disk space and time to read the data in the post-processing phase.

At the AIAA SciTech 2016 conference this month, I shared our in situ work with the AIAA community in two ways: I presented a paper to the MVCE technical committee titled, "In Situ Infrastructure Enhancements for Data Extract Generation", and I presented an in-booth talk about how to add in situ processing into a solver.

Many of the engineers I met at this year's SciTech are running codes at scale on high performance computers but find it impractical, often impossible, to save all of the data on such systems. In situ enables operations such as visualization and analysis, which have traditionally been performed as post-processing, to be executed in the solver itself as it runs. Instead of writing large amounts of volume data, in situ enables the creation of smaller data products such as images and FieldView XDB extract files. XDB files, for example, capture surfaces of interest as well as scalar and vector fields from the solver and write that data in a compact form orders of magnitude smaller than the standard results file.

GT Rotor visualization. Iso surfaces of Q, colored by Cp. Bottom left includes a cross plane of the mesh.

The paper I presented to the MVCE technical committee, "In Situ Infrastructure Enhancements for Data Extract Generation", describes enhancements made by Intelligent Light to VisIt/Libsim that improve its support for batch-creation of VisIt plots, which can then be exported as XDB extracts. Working with James Forsythe of the US Navy's NAVAIR, the CREATE-AVTM Kestrel solver was instrumented with the latest VisIt/Libsim enhancements for batch support and parallel data writing. Kestrel was run at scales up to 1024 cores using a workflow that produced XDB files every 5 solver iterations, an output frequency far higher than would be attempted with volume-based outputs. Even with writing extracts so often, the in situ production of extract files consumed less than 3% of the overall solver runtime. The set of extract files for a single time step is also 21 times smaller than the corresponding volume data, saving both disk space and time to read in large files for subsequent visualization. Several instances of FieldView operating concurrently processed the resulting XDB files into a movie showing helicopter rotor vortices. One strength of this workflow is that it is parallel from data extraction to extract I/O, all the way through XDB visualization. In addition, the workflow is flexible because XDB extracts provide both geometry and fields that can be visualized, enabling fast data analysis that skips the burden of large I/O using volume data.

Intelligent Light's recent VisIt/Libsim improvements make the process of instrumenting a simulation for in situ simpler than ever before. During the SciTech exhibition, I held a talk in the Intelligent Light booth about how to add in situ processing into a solver. The presentation was well attended by users and solver developers from the US, Japan and Israel. There was much interest in adding VisIt/Libsim and XDB data extraction to solvers and the workflow continues to prove its value.

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FieldView 16 and XDBview 2 Now Available

3D PDF export generated in FieldView and seen in Adobe Acrobat Reader® (left) and on a tablet (right). (DrivAer geometry courtesy of TU München, Mesh and simulation by VINAS with Pointwise and Helyx).

3D PDF export, faster data read, reduced memory usage and many more improvements

Just a little less than a year has passed by since our release of FieldView 15 and I am happy to announce that our new version, FieldView 16, is ready for download. While software users sometimes feel like installing a new version is not going to impact them much, I am confident that every single FieldView user will benefit from this release.

You will find that FieldView 16 is faster to read your data than previous versions and will also use less memory. Data read can easily be made even faster and more memory efficient by selecting the right Data Input option. When you don't need to perform Dataset Sampling or to compute a lot of streamlines, select "Less" Grid Processing for faster data input. In cases when you do need that kind of performance, select "More" right from the Data Input panel and you will use more memory to get better performance during you session.

FieldView 16 is the first CFD post-processor to introduce a built-in 3D PDF export. This standard format is a great way to present and share your results, allowing interactive exploration via rotation, zooming, panning and commenting in Adobe Acrobat Reader and in 3D PDF viewer apps.

Other highlights of this release include:

  • New Vertices and Shaded Vertices display types for better insight and fast performance
  • The ability to sweep surfaces coming from an XDB extract and to synchronize this operation between multiple datasets for easy animations and side-by-side comparison
  • More control over the location of Surface Flows
  • A new Growing display type for pathlines animation
  • 10x faster read times for AcuSolve users, compared to FieldView 15
  • The ability to read single-file transient data as steady-state
  • Support for results from FLOW-3D v11

We're also introducing the second version of XDBview. Our free, sharable viewer for XDB extracts, now includes the same sweep capability as FieldView 16 and can now read your CAD geometries in STL format.

To learn more about these new versions, I encourage you to read our What's New in FieldView 16 document (Japanese version).

FieldView 16 is a major release. You will need to request new passwords from Intelligent Light. FieldView 16 passwords will work for both version 15 and 16, but as of this release FieldView version 14 and earlier are no longer supported. If you need to test FieldView 16 with your data or workflows before upgrading, feel free to request additional temporary passwords and we'll be happy to provide them free of charge.

Please contact our FieldView Support Team  or your account manager for more information.


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