Particle Animation and Rendering Using Data Parallel Computation Karl Sims Optomystic Thinking Machines Corporation Presentation ©2001 Brenden Schubert

How many processors? The Thinking Machines Corporation Connection Machine CM-2 4,000-64,000 processors 512 MB memory Nodes arranged in hypercube TMC filed chapter 11 in 1994

Particles Head Position Tail Position (motion blur) Velocity Optional Characteristics: Type Mass Age Color Opacity Size Age to die at Whatever the simulation needs

Initialization of Position –Randomly distributed within a solid or sphere –Randomly distributed on surface of a solid or sphere –One particle on each vertex of a polygonal model –Randomly on surface of a polygonal model –3D Transformation from given coordinates Velocity –Constant Direction (including 0) –Randomly distributed within a solid or sphere –Randomly distributed on surface of a sphere

Applying Velocity Changes position parameter of particle, doesn’t change velocity parameter Examples: –Constant translation/rotation/scaling –Random translation/rotation/scaling –The Vortex Rotation proportional to distance from vortex axis

Applying Acceleration Changes velocity parameter of particle Examples: –Constant acceleration (gravity) –Random acceleration –Orbit around a point or axis –Spiral around a point or axis –Damping/Undamping –Bounce off of a plane/sphere/other object

Bouncing Crude method –Particles can penetrate surface of object –Particles reappear as if they travelled within object The better method –Interpolate to find intersection with object surface –Update velocity after hit to reflect friction and resilience parameters –Update positions to account for bounce –Bring tail position up to surface of object (if needed)

Particle Rendering What is a particle? –Particles occupy an area in which the opacity falls off from 1 at center to 0 at edges –Function determines rate of opacity falloff (e.g. Linear or Gaussian) Motion Blur –Render particle as streak, linearly interpolating all parameters between the head and tail positions

Slicing and Dicing What is a fragment? –Contribution of a particle to a pixel –Attributes: color, opacity, depth Fragment Generation –Slice each particle horizontally into spans –Dice each span vertically into fragments For each pixel –Sort fragments by depth –Calculate final pixel color

Patches Data parallel programming paradigm says that each object occupies a processor But the total number of fragments is often more than the number of processors Solution: –Split image into patches such that all objects for each patch can fit onto the processors –Render patches in sequence

Pseudocode Create Particles Initialize Particles –Set tails to previous heads –For each simulation time increment Select subset of particles –Perform operations Update positions using velocities Select subset of particles –Perform bounce operations –Adjust tails for motion blur shutter speed –Transform to screen coordinates –For each horizontal patch Determine effective patch height Dice particles into spans For each vertical patch –Determine effective patch width –Dice spans into fragments –Sort fragments by pixel and depth –Perform hidden surface calculation –Send colors to pixels –Add background color –Swap buffers For each frame:

Results: Snow and Wind

Results: Falling Water

Results: Waterfall

Results: Fire

Results: other

In Conclusion Future (at least in 1990) work –Allow particle-particle interaction Collisions Gravity –Interaction with polygonal objects Comparison to large-scale particle simulation on a serial computer Applicable to distributed computing