Parallel Solution to the Radiative Transport
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Parallel Parallel Solution to the Solution to the Radiative Radiative Transport Transport Szirmay-Kalos László Liktor Gábor Tamás Umenhoffer Tóth Balázs Glenn Lupton Kumar Shree EG PGV 2009 TU Budapest
description
Parallel Solution to the Radiative Transport. EG PGV 2009. Szirmay-Kalos László Liktor Gábor Tam ás Umenhoffer Tóth Balázs Glenn Lupton Kumar Shree. TU Budapest. Overview. Radiative transport Challenges of parallel iteration Our approach Initial estimation Modified iteration - PowerPoint PPT Presentation
Transcript of Parallel Solution to the Radiative Transport
Parallel Parallel Solution to the Solution to the Radiative Radiative TransportTransportSzirmay-Kalos László Liktor GáborTamás UmenhofferTóth BalázsGlenn Lupton Kumar ShreeEG PGV 2009
TU Budapest
OverviewOverview
Radiative transport Challenges of parallel iteration Our approach
– Initial estimation– Modified iteration– FCC GRID– CUDA
Results
AbsroptionOut-scatteringIn-scatteringEmission
Radiative transportRadiative transport
path: dsIncident radiancia:
L(s)
Outgoing radiancia:
L(s+ds)
Camera
screen
Solution methodsSolution methods
Monte-Carlo simulation– O(m -0.5)– Parallelization is
trivial Iteration
– O(m)– Parallelization is
a challenge
IterationIteration
Finite-element approaches (grid)
Iteratively refines the estimation
Error depends on the initial guess
L = TL + Q
Ln= TLn-1 + Q
||Ln-L||<n ||L0-L||
Parallel IterationParallel Iteration
Costly data exchanges Less frequent data
exchanges Few iteration steps:
Good initial guess– Unscattered component– Homogeneous solution– Approximate
inhomogeneous
node1
node2
node3
node4
Boundary affecting multiple
blocks
Initial approximationInitial approximation
Direct term Direct + Indirect
Solve diff. equation for each ray assuming spherical symmetry
Iteration refinement - Iteration refinement - Finite element: Finite element: FCC FCC gridgrid
CC
BCC FCC
Ln-12
Reduced data Reduced data exchangesexchanges
T1
T2
T21
T12
TLn-1+QLn Ln-1
node1
node2
node3
node4Ln2
Ln1 Ln-1
1
Ln-22
Reduced data Reduced data exchangesexchanges
TLn-1+QLn
T[T12](Ln-3-Ln-2)
TLn-2+Q+ TLn-2+Q
Noise converges to zero!
Iteration solutionIteration solution: CUDA: CUDA
Sampling
Sampling
Illumination network
Iteration solutionIteration solution: CUDA: CUDA
Sampling
Illumination network
Initial radiance distribution
Iteration solutionIteration solution: CUDA: CUDA
Sampling
Illumination network
Initial radiance distribution
Iteration
Iteration solutionIteration solution: CUDA: CUDA
Sampling
Illumination network
Initial radiance distribution
Iteration
Visualization
Iteration solutionIteration solution: CUDA: CUDA
Visualization: Visualization: 5 node HP SVA5 node HP SVA
node 1
node 2
…
Error analysis for the Error analysis for the initial distributioninitial distribution
ScalabilityScalability Single iteratio
n
Error2%
Compute + Communication
ResultsResultsDirect term
100 iterations 25 iterations
Direct+Indirect estimation
ConclusionsConclusions
Interactive solution of the radiation transport
Scalable iteration scheme
Current limitations– No specular reflections– Point sources
