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Integrating GPGPU Functionality into Scene Graphs PowerPoint PPT Presentation


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Jens Orthmann , Maik Keller, Andreas Kolb Computer Graphics and Multimedia Systems University of Siegen. Integrating GPGPU Functionality into Scene Graphs. Motivation. Evolution of generic GPGPU languages Heterogeneous architectures (OpenGL + CUDA)

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Integrating GPGPU Functionality into Scene Graphs

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Integrating gpgpu functionality into scene graphs

Jens Orthmann, Maik Keller, Andreas Kolb

Computer Graphics and Multimedia Systems

University of Siegen

Integrating GPGPU Functionality into Scene Graphs


Motivation

Motivation

  • Evolution of generic GPGPU languages

  • Heterogeneous architectures (OpenGL + CUDA)

  • Scene graphs are the most frequently used graphics architectures

  • General purpose functionality for scene graphs

    ( Physics, Simulations, Ray Tracing, Image Processing, Visualization )

NVSG by NVidia

VolumeViz by Mercury

XIP by Siemens


Contexts

Contexts

  • A scene graph is populated with different kinds of rendering resources.

    (textures, geometry, etc.)

  • Developers need to map these resources to the CUDA or OpenCL context

  • Interoperability should be invisible for developers.

  • The interface should be small.

Rendering

Computation


Graph integration

Graph Integration

  • How to integrate computations into the graph?

  • How to identify resources?

  • How to manage dynamic structures?

?


Approaches

Approaches

Callback Approach

Engine Approach

Subtraversal Approach

  • SmallInterface

  • Fixed References

  • No Intracommunication

  • Intracommunication

  • Multiple resources

  • Hidden dependencies

  • Fixed References

  • No references

  • Intracommunication

  • Multiple resources

  • Visible dependencies

  • Requires traversals

  • Naming scheme

’’Input’’

’’Input’’

’’Output’’


Subtraversal approach

Subtraversal Approach

Single Context

Shared Context

Multiple Contexts


Resource gathering

Resource Gathering

  • Resources are passed on to the computation modules

  • Exchange current computation context


Graph evaluation

Graph Evaluation

  • Resources are mapped during the computation

  • Abstract view of resources within computations


Resource mapping

Resource Mapping

  • Intermixing rendering with computations

  • Memory mapping between contexts is expensive


Results

Results

osgCompute:

  • CUDA (2.3) integration into OpenSceneGraph

  • Useable without the Scenegraph structure (similar to the Thrust API)

  • Support for all platforms: Linux, Mac, Windows

  • Framework, documentation and examples are available under the LGPL:

    http://www.cg.informatik.uni-siegen.de/svt/osgcompute

    Current Research:


Thank you for your attention

  • This work is partially funded by the Siegener Graduate School “Development of Integral Heterosensor Architectures for the n-Dimensional (Bio)chemical Analysis”.

  • Thanks to Robert Osfield and Art Tevs for their support

Thank you for your attention!


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