Intelligent Light and FieldView

NVIDIA and Intelligent Light Pushing Ahead with In Situ Rendering on Servers

NVIDA developer blog has a feature about server side rendering featuring our work with customers such as Daimler AG.
"Intelligent Light and Daimler AG use server-based pipelines to analyze the results of their large-scale vehicle simulations. To validate thermal operating bounds when designing new vehicles, Intelligent Light's FieldView can be used to visualize the results of highly-parallel simulations. Sifting through the 15 terabytes of data from this simulation is much more quickly done on the server that ran the simulation, after which the salient time steps can be extracted and used to visually communicate results.​"
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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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