GPU ParticlesJason Lubken

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ParticlesNvidia CUDA SDK

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ParticlesNvidia CUDA SDK

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SPHSmoothed Particle Hydrodynamics

Nvidia PhysX SDK

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SPHSmoothed Particle Hydrodynamics

Nvidia PhysX SDK

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Advection, Wind Fields& Weather Effects

GPU RainfallPierre Rousseau, Vincent Jolivet, Djamchild Ghazanfarpour 2008

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Problem

Problem: CPU - GPU communication is too slow for particles

Move everything to the GPU

Problem: Manage computation & storage for potentially O(n2) particle interactions

Optimize & tune

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Papers

UberFlow: A GPU-Based Particle Engine

Peter Kipfer, Mark Segal, Rüdiger Westermann

Fast N-Body Simulation with CUDA

Lars Nyland, Mark Harris, Jan Prins

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UberFlow

Particle creation

Particle movement

Particle sorting for depth or particle interaction

(Optional) Particle interaction

Boundary enforcement

Rendering

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UberFlow

Particle creation

Particle movement

Particle sorting for depth or particle interaction

(Optional) Particle interaction

Boundary enforcement

Rendering

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Particle Creation

Encode particle properties in one or more textures

Position (RGB)

Creation time (A)

Velocity (RGB)

Type (A)

Cycle particle regeneration using modulo

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UberFlow

Particle creation

Particle movement

Particle sorting for depth or particle interaction

(Optional) Particle interaction

Boundary enforcement

Rendering

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Particle Movement:Euler Integration

Iterative

Storage:

Velocity × 2

Position × 2

Update:

v = v’ + a ⋅ ∆t

p = p’ + v ⋅ ∆t

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UberFlow

Particle creation

Particle movement

Particle sorting for depth or particle interaction

(Optional) Particle interaction

Boundary enforcement

Rendering

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Sorting for Depth

Assign an id to each particle

Compute distance to viewer

Bitonic sort on distance --retain id--

Move position & velocity storage

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Assigning Ids

Problem: After sorting, find a particle’s original location in a large texture using only a single float id

Distance between consecutive float values is not constant

Millions of particles > 65,536 particles

One bit of exponent is not enough

Precompute the texture of unique ids on the CPU

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UberFlow

Particle creation

Particle movement

Particle sorting for depth or particle interaction

(Optional) Particle interaction

Boundary enforcement

Rendering

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Adding Sorting Keys

Problem: Resolve collisions without O(n2) comparisons

Construct spacial keys

Like: x/g2 + y/g + z

First use aligned cells

Then use staggered cells

Resolve collisions

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UberFlow

Particle creation

Particle movement

Particle sorting for depth or particle interaction

(Optional) Particle interaction

Boundary enforcement

Rendering

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UberFlow

Rotation & rotational velocity

Particle types

Surface normal

Color

Shape

Wind field

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UberFlow

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UberFlow

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Papers

UberFlow: A GPU-Based Particle Engine

Peter Kipfer, Mark Segal, Rüdiger Westermann

Fast N-Body Simulation with CUDA

Lars Nyland, Mark Harris, Jan Prins

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N-Body Simulation

All particles effect one another directly

Brute force without spacial partitioning: O(n2)

Simplification using far-field effects possible

No collision detection

Integration problems with close proximity & high force

Eplison check & different integrator used

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Force Computation

fij = G ( (mi mj) / |rij|2 ) ⋅ ( rij / |rij| )

mi & mj are mass

r is distance between particle i and particle j

G is gravitational constant

First term is force

Second term is direction

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Force Optimization

CPU does half the computation

Leapfrog-Vertlet integration

Smoother than Euler integration

Particle positions & acceleration needed --no velocity texture lookup--

Remove mi from computation

Work to overcome integration problems at close proximity also removes fii

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Summation Optimization

Tile computation of gravitational force

Loop unrolling 32 body-body interaction

Split rows for small N

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N-Body Simulation

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N-Body Simulation

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Ideas

UberFlow

“Clever” use of ids seems computationally intensive

How do you tune this?

N-Body Simulation

Force splatting to alpha buffer

Particle control from CPU using small texture

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References

UberFlow: A GPU-Based Particle Engine 2004, Peter Kipfer, Mark Segal, Rüdiger Westermann 2004 http://wwwcg.in.tum.de/Research/Publications/UberFLOW

Fast N-Body SImulation with CUDA, Lars Nyland, Mark Harris, Jan Prins 2008 http://http.developer.nvidia.com/GPUGems3/gpugems3_ch31.html (GPU Gems 3)

Everything About Particle Effects, Lutz Lata 2007 http://www.2ld.de/gdc2007/

Broad Phase Collision Detection with CUDA, Scott Le Grand 2008 http://http.developer.nvidia.com/GPUGems3/gpugems3_ch32.html (GPU Gems 3)

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Particle Movement

Closed or Parametric Form

Vertlet Integration

Euler Integration

Others

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Particle Movement:Vertlet Integration

Iterative

Storage:

Position × 3

Update:

p = 2p’ - p’’ + a ⋅ ∆t2

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Particle Movement: Closed or Parametric Form

Stateless

Storage:

Position x 2

Velocity

Update:

p = po + vot + ½a ⋅ t2

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