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A Particle System for Interactive Visualization of 3D Flows

A Particle System for Interactive Visualization of 3D Flows. Authors:. Jens Kr ü ger Peter Kipfer Polina Kondratieva R ü diger Westermann. Presented By:. Hector M. Garcia. Problem.

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A Particle System for Interactive Visualization of 3D Flows

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  1. A Particle System for Interactive Visualizationof 3D Flows Authors: Jens Krüger Peter Kipfer Polina Kondratieva Rüdiger Westermann Presented By: Hector M. Garcia MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  2. Problem • In flow research and industrial practice vector field data is one of the key sources for the analysis of flow field dynamics • Visual exploration of complex fields imposes significant requirements on the visualization system and demands for approaches capable of dealing with large amounts of vector valued information at interactive rates. • Previous approaches to virtually explore high-resolution flow fields lack the ability to simultaneously advect and display large amounts of particles. MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  3. Advection • Advection is transport in a fluid • The fluid is described mathematically for such processes as a vector field, and the material transported is described as a scalar concentration of substance, which is present in the fluid. • A good example of advection is the transport of pollutants or silt in a river: the motion of the water carries these impurities downstream. MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  4. Motivation • Overcome current methods limitations by exploiting features of recent graphics accelerators to advect particles in the graphics processing unit (GPU). • Ability to achieve interactive streaming and rendering of millions of particles using higher order numerical integration schemes. • Enable the virtual exploration of large fields in a way similar to real-world experiments. MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  5. Motivation MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  6. Some background info… • GPU = Graphics Processing Unit. • It is a dedicated graphics rendering device. • GPUs have a highly parallel structure which makes them more effective than typical CPUs for a range of complex algorithms. MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  7. More background info… • Recent developments in GPUs include support for programmable shaders • Because most of these computations involve matrix and vector operations, engineers and scientists have increasingly studied the use of GPUs for non-graphical calculations. • Applications requiring massive vector operations, can make use of the massive floating-point computational power of a GPU. This can yield several orders of magnitude higher performance than a conventional CPU. MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  8. Related Work • Particle tracing techniques for flow viz have been studied intensively. • Core of these techniques use numerical integration schemes. • In flow viz context, analysis of such schemes with respect to stability,accuracy and performace. MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  9. Related Work (cont’d…) • Particle-based techniques can visualize local features in the flow. • Global imaging techniques for 3D fields can illustrate global behavior. • LIC-methods allow for interactive 2D vector fields but no good in 3D flow. MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  10. Related Work (cont’d…) MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  11. Methods • Propose a method for overcoming both computation and bandwidth limitations using the GPU. • Use GPU for advection and rendering computations. • Use improvements to rendering pipeline. MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  12. Methods (cont’d…) MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  13. Methods (cont’d…) • Using this functionality, particle tracing can be performed entirely on the GPU. • Their method computes intermediate results saves them in texture memory and uses them again as input to the geometry units to render images in the frame buffer. • Initial particle positions stored in RGB texture of size M x N. • User defines number of particles and appropriate texture is generated on the CPU and uploaded on the GPU. • Particle Integration • Incarnation • advection MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  14. Methods (cont’d…) MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  15. Methods (cont’d…) • Particle Incarnation • Transformation • Birth • Update • Particle Advection • Texture access • Death test • Advection • Reincarnation MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  16. Methods (cont’d…) • GPU particle engine for flow viz is implemented in Cg MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  17. Methods (cont’d…) MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  18. Methods (cont’d…) • Particle Rendering • OpenGL SuperBuffer • Memory object is bound as the current texture render target and as a vertex array used to draw particle primitives. • Vertex Texture Fetch • The key concept is to let the fragment units generate textures and to use these textures as displacement maps for geometric primitives in subsequent rendering passes. MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  19. Methods (cont’d…) • Rendering • Points • Maximum number of particles stored in video memory rendered as color primitives is 250 million per second • Oriented Point Sprites • Used to reveal flow direction. • Use a sprite texture atlas for arbitrary shaped geometry MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  20. Point Rendering MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  21. Oriented Point Sprite Rendering MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  22. Sorting • Authors implement a GPU sorting network into their particle engine. • Based in the Bitonic merge sort algorithm. • Well suited for GPU architecture because sequence of operations is fixed and not dependent in the data to be sorted. MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  23. What is Bitonic merge sort? • Data independent sorting method based on the bitonic sequence • A 0-1-sequence is called bitonic, if it contains at most two changes between 0 and 1. • More generally, a sequence of numbers is bitonic sequence if it has at most one local maximum or one local minimum. • Examples: 1,2,3,4,5 ; 10,6,5,3,1 ; 3,7,9,8,6,5,4,1 10,8,6,9,12,15,20 MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  24. How does it look like ? MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  25. Derived Flow attributes • Velocity • Divergence • Enstrophy • 2 MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  26. Derived Flow attributes (contd…) MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  27. Visualization Geometry • Stream Lines • Ping pong buffer (double buffer) • Texture samples interpreted as control points • Draw polylines of T control points • Stream Ribbons • Show rotation about the flow axis • Build a second atlas that contains the other rim of each stream line rotating the initial normal vector according to the accumulated increment angles. MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  28. Stream Lines MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  29. Stream Ribbons MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  30. Evaluation • Model runs at interactive rates on PC hardware • It outperforms CPU counterparts • Show timing statistics to compare their GPU implementation vs. CPU. MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  31. Evaluation (cont’d…) • Lets take a test drive ! MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  32. Conclusion • Authors successfully demonstrates advantages of a GPU implementation of a particle flow simulation. • The possibility of integrating numerically and data intensive computations for flow analysis into the rendering process distinguishes the GPU engine from previous approaches. MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  33. Conclusion (cont’d…) • Besides particle advection, the engine provides a variety of visualization options to visually convey relevant structures in 3D steady flow fields. • By using massive particle sets in combination with oriented sprites, LIC-like visualizations can be achieved at interactive rates. This includes higher order integration schemes, thus providing numerically accurate particle traces. MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  34. Questions • Given the parallel architecture of GPUs would a GPU cluster method help for visualizing massive global 3D flow visualizations? MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  35. Questions (cont’d…) • How would the performance of the visualization engine be impacted if the vector field is fed by a fully functional numerical model. i.e. ROMS MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

  36. Questions (cont’d…) • Could their implementation be easily extended to non-uniform grids ? MSIM 842 VISUALIZATION II INSTRUCTOR: JESSICA R. CROUCH

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