TUVOK and ImageVis3D
J. Krüger1, T. Fogal1, B. Whitlock2
1
SCI Institute, University of Utah; 2Lawrence Livermore National Laboratory
Summary
Scientists from the SciDAC Visualization and Analytics Center for Enabling Technology (VACET) have
developed cutting-edge techniques for visualizing large volume data. These new approaches leverage
recent standards in GPU processing technology, allowing interactive visualization capabilities for datasets
which previously only achieved interactivity in specialized research environments. Ongoing work is
underway to integrate these tools into production-quality general purpose visualization and analysis tools,
such as the VisIt software package.
Large Scale Data
Volume data are inherently difficult to visualize
in a generic manner. Two prominent approaches are
volume rendering, which considers the dataset an
amorphous mass, and isosurfacing, which empowers
a user to extract a surface of the dataset which
embodies a particular characteristic.
Both approaches have the drawback of
computational complexity: they must examine all of a
dataset to generate the desired image. Further, with
the advent of petascale class machines, scientists are
generating simulation data at unprecedented
resolution. Combined, these two components make
visualizing large scale scientific volume data ever
more difficult.
Yet the importance of performing these rendering
modes in real-time is paramount. Despite promising
research in automatically developing informative
visualizations, the process of determining effective
settings which highlight features of interest is an
exploratory one. As such, it is critical for a
visualization tool to allow real-time modification of
these settings, to aid in this free-form process of
discovery.
Figure 1. Tuvok using its 'ClearView' rendering
mode. ClearView suits the focus + context model,
popular in large scale scientific visualization,
through an intuitive model of a lens which can see
`in' to the dataset. In this data, scientists can
rapidly discern the internal behavior of a
Richtmyer-Meshkov simulation at the interface,
while simultaneously viewing the global structure
of the fluids.
Approaches
There are many approaches to dealing with this explosion of data in a manner which creates a useful
tool for researchers. One way is to rely on special-purpose hardware, but this adds to system complexity
and is generally a poor long-term investment. A better strategy is to utilize advanced data structures and
algorithms which can efficiently map these rendering techniques onto commodity systems. We have
invested in the latter.
Tuvok is a volume rendering library which harnesses the immense recent progress made with
commodity general purpose graphics processing devices. Designed from the ground up to handle data at
this scale, Tuvok's advanced level-of-detail and bricking schemes provide an out-of-core solution to the
problem of rendering large data. All of this is provided in a production-quality library which is simple to
understand, integrate into existing software packages, and modify to take advantage of new advances in
visualization research.
The hallmark of these is the out-of-core techniques of the volume renderer. Such a renderer is a
technical challenge because it may not assume it is possible to load an entire dataset into main memory, a
plausible case in the scale of data we deal with. To deal with this challenge, VACET has developed
Tuvok to effectively represent data at multiple levels of detail, using a bricking scheme which is both
simple and powerful.
ImageVis3D, Tuvok's first client application, is a complete software product already in daily use by
many scientists to cope with and understand their data. Using ImageVis3D provides researchers an
expedient way to highlight the regions that are important for them, in some cases allowing them to focus
on regions which no other tool can effectively visualize. Real-time editing of visualization parameters
encourages users to explore their datasets, replacing rigid, manual processes with a flexible, interactive
one. Finally, Tuvok's ray casting rendering mode creates images of the highest visual quality, suitable for
production-quality publications.
Future
Work is currently underway to integrate Tuvok into the production visualization and analysis tool,
`VisIt', already in wide use among VACET stakeholders. This provides a vehicle by which users can
transparently take advantage of VACET technology. When completed, users will be able to take
advantage of Tuvok's hardware accelerated rendering to ascertain characteristics of their data with ease.
On the horizon is the integration of Tuvok's highly efficient graphics processing unit (GPU) ray
casting with VisIt's rich support for data parallelism. Existing support leverages DOE parallel computing
platforms to provide high quality renderings of extremely large data, but is limited in its ability to take
advantage of all available resources. As `GPU clusters' (clusters with 1 or more high-powered GPUs per
node) become more prevalent, software must take full advantage of these additional new resources to
remain capable of dealing with these challenging datasets. We are developing a framework to allow VisIt
to scale to current architectures and beyond, as the price/performance ratio of GPUs makes such clusters
more attractive every year.
Recent Publications
J. Krüger, K. Potter, R. MacLeod, C.R. Johnson, “Unified Volume Format: A General System For
Efficient Handling Of Large Volumetric Datasets.” Proceedings of The International Conference on
Computer Graphics and Visualization (IADIS), 2008
J. Krüger, J. Schneider, R. Westermann, “ClearView: An Interactive Context Preserving Hotspot
Visualization Technique.” IEEE Transactions on Visualization and Computer Graphics (Proceedings of
IEEE Visualization 2006)
K. Bürger, J. Krüger, R. Westermann, “Direct Volume Editing.” IEEE Transactions on Visualization and
Computer Graphics (Proceedings of IEEE Visualization 2008)
For further information on this subject contact:
Name: T. Fogal.
Organization: SCI Institute, University of Utah
Email: tfogal@sci.utah.edu
Phone: (801) 585-3950
Note: This work was funded in part by the SciDAC2 Visualization and Analytics Center for Enabling Technologies and ASCR’s Visualization
Base Program by the Director, Office of Science, Office of Advanced Scientific Computing Research, of the U.S. Department of Energy under
Contract No. DE-AC03-76SF00098.