Steven F. Ashby Center for Applied Scientific Computing Month DD, 1997

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Steven F. Ashby Center for Applied Scientific Computing Month DD, 1997 Powered By Docstoc
					           R-LODs:
 Fast LOD-based Ray Tracing of
        Massive Models
Sung-Eui Yoon
Lawrence Livermore National Lab.

Christian Lauterbach
Dinesh Manocha
Univ. of North Carolina-Chapel Hill
 Goal
 ● Perform an interactive ray tracing of
   massive models
    ● Handles various kinds of polygonal meshes
      (e.g., scanned data and CAD)




 St. Matthew   Double eagle tanker
372M triangles   82M triangles       Forest model (32M)   2
Recent Advances for Interactive
Ray Tracing
● Hardware improvements
  ● Exponential growth of computation power
  ● Multi-core architectures
● Algorithmic improvements
  ● Efficient ray coherence techniques [Wald et al.
    01, Reshetov et al. 05]




                                                      3
Hierarchical Acceleration Data
Structures
● kd-trees for interactive ray tracing [Wald
  04]
  ● Simplicity and efficiency
  ● Used for efficient object culling
                                    Axis-aligned
           kd-node                  bounding box




                                                   4
Ray Tracing of Massive Models
● Logarithmic asymptotic behavior
  ● Very useful for dealing with massive models
  ● Due to the hierarchical data structures
  ● Observed only in in-core cases




                                                  5
Performance of Ray Tracing with
Different Model Complexity
● Measured with 2GB main memory


               Render time             Memory
                (log scale)           thrashing!



             Working set
                size                  2GB



       Model complexity (M tri) - log scale
                                                   6
Low Growth Rate of
Data Access Time
                 Growth rate
              during 1993 – 2004
  50
  45
  40                                           47X
  35
  30
  25
  20
  15
  10     2X                20X
   5
   0

        Disk             RAM                  CPU
       access           access               speed
       speed            speed

        Courtesy: http://www.hcibook.com/e3/online/moores-law/   7
Inefficient Memory Accesses and
Temporal Aliasing
● St. Matthew (256M triangles)
  ● Around 100M visible triangles

● 1K by 1K image resolution
  ● 1M primary rays
  ● Hundreds of triangle per pixel
  ● Each triangle likely in different
    area of memory




                                        8
Main Contributions
● Propose an LOD (level-of-detail)-based ray
  tracing of massive models
  ● R-LOD, a novel LOD representation for Ray
    tracing
  ● Efficient LOD error metric for primary and
    secondary rays
  ● Integrate ray and cache coherent techniques




                                                  9
Performance of Ray Tracing with
Different Model Complexity
● Measured with 2GB main memory


               Render time             Memory
                (log scale)           thrashing!



             Working set
                size                   2GB



       Model complexity (M tri) - log scale
                                                   10
Performance of LOD-based Ray
Tracing
  Achieved up to three order of magnitude speedup!
● Measured with 2GB main memory


                Render time
                 (log scale)




           Working set
              size


        Model complexity (M tri) - log scale
                                                     11
Real-time Captured Video – St.
Matthew Model




    512 by 512 and 2x2 super-sampling,
    4 pixels of LOD error in image space   12
Related Work
● Interactive ray tracing
● LOD and out-of-core techniques
● LOD-based ray tracing




                                   13
Interactive Ray Tracing
● Ray coherences
  ● [Heckbert and Hanrahan 84, Wald et al. 01,
    Reshetov et al. 05]
● Parallel computing
  ● [Parker et al. 99, DeMarle et al. 04, Dietrich et
    al. 05]
● Hardware acceleration
  ● [Purcell et al. 02, Schmittler et al. 04, Woop et
    al. 05]
● Large dataset
  ● [Pharr et al. 97, Wald et al. 04]

                                                        14
LOD and Out-of-Core Techniques
● Widely researched
  ● LOD book [Luebke et al. 02]
  ● Out-core algorithm course [Chiang et al. 03]
● LOD algorithms combined with out-of-core
  techniques
  ● Points clouds [Rusinkiewicz and Levoy 00]
  ● Regular meshes [Hwa et al. 04, Losasso and
    Hoppe 04]
  ● General meshes [Lindstrom 03, Cignoni et al.
    04, Yoon et al. 04, Gobbetti and Marton 05]

       Not clear whether LOD techniques
  for rasterization is applicable to ray tracing   15
 LOD-based Ray Tracing
 ● Ray differentials [Igehy 99]
    ● Subdivision meshes [Christensen et al. 03, Stoll
      et al. 06]
    ● Point clouds [Wand and Straβer 03]


      Image plane
                                         Footprint size
Viewpoint                                   of ray


             Ray beam for one pixel


                                                          16
Outline
● R-LODs for ray tracing
● Results




                           17
Outline
● R-LODs for ray tracing
● Results




                           18
 R-LOD Representation
 ● Tightly integrated with kd-nodes
    ● A plane, material attributes, and surface
      deviation
                             Rays

                                       kd-node


     No                                          Plane
intersection

                              Normal   Valid extent
               Intersection            of the plane
                                                         19
Properties of R-LODs
● Compact and efficient LOD representation
  ● Add only 4 bytes to (8 bytes) kd-node

● Drastic simplification
  ● Useful for performance improvement

● Error-controllable LOD rendering
  ● Error is measured in a screen-space in terms of
    pixels-of-error (PoE)
  ● Provides interactive rendering framework


                                                      20
Two Main Design Criteria for
LOD Metric
● Controllability of visual errors
● Efficiency
  ● Performed per ray (not per object)
  ● More than tens of million times evaluation




                                                 21
Visual Artifacts
● Visibility difference   Surface deviation
● Illumination difference Projected area
                                           Curvature
● Path difference for secondary rays       difference
                                   View direction
  Original mesh                    Ray with original mesh

                                   Ray with LODs

LODs


                             Image plane
                                                            22
R-LOD Error Metric
● Consider two factors
  ● Projected screen-space area of a kd-node
  ● Surface deviation




                                               23
Conservative Projection Method
● Measures the screen-space area affected by
  using an R-LOD
                                 ?
          LOD metric: C (B) dmin > R

              Image plane

                            dmin
Viewpoint                              R
                                           kd-node
                   B{
 PoE error bound
                        One ray beam
                                                24
  R-LODs with Different PoE
  Values




PoE: Original       1.85              5       10
                (512x512, no anti-aliasing)        25
LOD Metric for Secondary Rays
● Applicable to any linear transformation
  ● Shadow
  ● Planar reflection



● Not applicable to non-linear transformation
  ● Refraction
  ● Uses more general, but expensive ray
    differentials [Igehy 99]




                                                26
C0 Discontinuity between R-LODs
                           Ray




● Possible solutions
  ● Posing dependencies [Lindstrom 03, Hwa et al.
    04, Yoon et al. 04, Cignoni et al. 05]
  ● Implicit surfaces [Wald and Seidel 05]

                                                    27
Expansion of R-LODs
                            Ray




● Expansion of the extent of the plane
  ● Inspired by hole-free point clouds rendering
    [Kalaiah and Varshney 03]
  ● A function of the surface deviation (20% of the
    surface deviation)


                                                      28
Impact of Expansions of R-LODs
                                  Hole


                                     Before
                                    expansion




                                     After
                                   expansion


                     PoE = 5
 Original model
                  at 512 by 512            29
R-LOD Construction
● Principal component analysis (PCA)
  ● Compute the covariance matrix for the plane of
    R-LODs
                   Normal (= Eigenvector)




● Hierarchical PCA computation
  ● Has linear time complexity
  ● Accesses the original data only one time with
    virtually no memory overhead

                                                     30
Utilizing Coherence
● Ray coherence
  ● Using LOD improve the utilization of SIMD
    traversal/intersection

● Cache coherence
  ● Use cache-oblivious layouts of bounding
    volume hierarchies [Yoon and Manocha 06]
  ● 10% ~ 60% performance improvement




                                                31
Outline
● R-LODs for ray tracing
● Results




                           32
Implementation
● Uses common optimized kd-tree
  construction methods
  ● Based on surface-area heuristic [MacDonald
    and Booth 90, Havran 00]

● Out-of-core computation
  ● Decompose an input model into a set of
    clusters [Yoon et al. 04]




                                                 33
Preprocessing
● Simplification computation speed
  ● Very fast due to its linear complexity
    (3M triangles per min)

● Memory overhead
  ● Requires 33% more storage over the optimized
    kd-tree representation [Wald 04]

● Runtime overhead
  ● 5% compared to non-LOD version of the same
    efficient ray tracer

                                                   34
Impact of R-LODs
                             10X speedup
      # of intersected
      nodes per ray

    Render time



         Working set
            size



                         PoE = 0
                                                 35
                         (No LOD)    PoE = 2.5
Real-time Captured Video – St.
Matthew Model
   512 x 512, 2 x 2 anti-aliasing, PoE = 4




                                             36
Pros and Cons
● Limitations
  ● Does not handle advanced materials such as
    BRDF
  ● No guarantee there is no holes


● Advantages
  ● Simplicity
  ● Interactivity
  ● Efficiency



                                                 37
Conclusion
● LOD-based ray tracing method
  ● R-LOD representation
  ● Efficient LOD error metric
  ● Hierarchical LOD construction method with a
    linear time complexity
  ● Reduce the working set size




                                                  38
Ongoing and Future Work
● Investigate an efficient use of implicit
  surfaces
● Allow approximate visibility
● Extend to global illumination




                                             39
Acknowledgements
● Model contributors
● Funding agencies
  ●   Army Research Office
  ●   DARPA
  ●   Lawrence Livermore National Laboratory
  ●   National Science Foundation
  ●   Office of Naval Research
  ●   RDECOM
  ●   Intel
  ●   Microsoft


                                               40
Acknowledgements
● Eric Haines
● Martin Isenburg
● Dawoon Jung
● David Kasik
● Peter Lindstrom
● Matt Pharr
● Ingo Wald
● Anonymous reviewers



                        41
Questions?
             Thanks!




                       42
UCRL-PRES-223086

This work was performed under the auspices
of the U.S. Department of Energy by University
of California Lawrence Livermore National
Laboratory under contract No. W-7405-ENG-48.




                                                 43
Additional slides




                    44
Goal
● Perform an interactive ray tracing of
  massive models
  ● Handles various kinds of polygonal meshes
    (e.g., scanned data and CAD)

                      Double eagle tanker
                        82M triangles



                 St. Matthew
                372M triangles
                         Isosurface (472M)
                                                45
Memory Hierarchies
Size                       Speed

  1KB                        100 ns
              Register


  1MB         Caches         101 ns



   1GB      Main memory      102ns



  > 1GB     Disk storage     104ns

                                   46
Hierarchical R-LOD Computation
with Linear Time Complexity
                        n
          xy   ( xk   x )( yk   x ),
                       k 1
where    xk   ,   yk     are x, y coordinates of kth points
         n
                   2 n     n
                                 2                 n          n
 xy     xk y k   xk  y k  2               x y   k          k
         k 1      n k 1 k 1  n                 k 1       k 1


                                  +




                                                                        47
Performance Comparison – St.
Matthew Model

                                       2 ~ 20X
                                    improvements
                 Non-LOD
Render time
   (sec)



               LOD



              Approaching the model for every frame
                                                      48
Image Quality Comparison – St.
Matthew Model
        512 x 512, no anti-aliasing
     LOD (PoE = 4)                Non-LOD




                                            49
Further Information
● R-LODs: Fast LOD-based Ray Tracing of
  Massive Models
  ● S. Yoon, C. Lauterbach, and D. Manocha
  ● (To appear at) Pacific graphics (The Visual
    Computer) 2006




                                                  50
Recent Advances for Interactive
Ray Tracing
● Hardware improvements
  ● Exponential growth of computation power
  ● Multi-core architectures
● Algorithmic improvements
  ● Efficient ray coherence techniques [Wald et al.
    01, Reshetov et al. 05]




      These improvements may not provide
       an efficient solution to our problem!

                                                      51
Ray Coherence Techniques
● Assume coherences between spatially
  coherent rays
   ● Works well with CAD or architectural models

● Highly-tessellated models
   ● There may not be much coherence between
     rays
       Image plane
                                                Small
Viewpoint
                                              triangles


                Rays per each pixel                  52
 Ray Coherence Techniques
 ● Models with large primitives
    ● Group rays and test intersections between the
      group and a bounding box

                                               Large
            Image plane                      triangles
Viewpoint




                     Ray beams                        53
Ray Coherence Techniques
● Highly tessellated models
  ● Fall back to the normal ray tracing
  ● Causes incoherent memory accesses and
    temporal aliasing
                                          Small
        Image plane                     triangles

Viewpoint




                Ray beams                           54
Runtime Traversal with R-LODs
● Built on top of the efficient kd-tree
  traversal algorithm [Wald 04]

                      Check whether
                     the error is met?
                                   Check whether
                              there is an intersection?
                                   If intersected,
                                    return shading info
                                   Otherwise,
                                      stop traversal

      : kd-node w/ R-LOD       : kd-node w/o R-LOD        55
Two Main Design Criteria for
LOD Metric
● Controllability of visual errors
● Efficiency
  ● Model complexity: 100M (at least 27 deep kd-
    tree)
  ● Image resolution: 1k by 1K (= 1M rays)
  ● 27M (= 1M x 27) times of LOD metric
    evaluation!




                                                   56
Surface Deviation
● Combined with the previous projected-
  space error bound, R
                           New R


Plane of R-LOD




  Underlying
   geometry

                                          57
 Properties of R-LODs
 ● Compact and efficient LOD representation
    ● Add only 4 bytes to (8 bytes) kd-node

 ● Drastic simplification
    ● Useful for performance improvement
    ● Recursively simplify 23 triangles into one R-LOD

      kd-node w/ R-LOD

kd-node w/o                                    Simplify
   R-LOD


                                                          58
 Image Quality Comparison –
 Forest Model (32M Triangles)
           4 X speedup




PoE = 0 (No LOD)        PoE = 4          Shading
                   and cache-oblivious   difference
                    layout of kd-tree                 59
 Image Quality Comparison –
 Forest Model




PoE = 0 (No LOD)   PoE = 16   Shading
                              difference
                                           60
  R-LODs with Different PoE
  Values




PoE: Original            40                80
                512x512 image resolution        61

				
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