Lightspeed SIGGRAPH talk

The Lightspeed Automatic Interactive Lighting Preview System

Jonathan Ragan-Kelley / MIT CSAILCharlie Kilpatrick / ILM

Brian Smith / ILMDoug Epps / Tippett Studio

Paul Green / MIT CSAILChristophe Héry / ILM

Frédo Durand / MIT CSAIL

Lighting Design

■End of pipelinefixed geometry, viewpoint, material

■Slow feedback10-60 mins to render

1 hour later...

Lighting Design

■End of pipelinefixed geometry, viewpoint, material

■Slow feedback10-60 mins to render

another hour later...

Goal: Fast Lighting Preview

Exploit redundancy between previews■ geometry■ view■material

High-Level Approach

■Precompute deep-framebuffer cache

■Preview dynamically on GPUas the user specifies new light parameters

...e.g.

normal position diffusetexture

speculartexture

Prior Work

Parameterized Ray Tracing [Séquin & Smyrl 1989]

G-Buffer [Saito & Takahashi 1990]

Fast Relighting Engine [Gershbein & Hanrahan 2000]

■Precomputed buffer(normals, texture)with BRDF*light reevaluated at runtime

■Shortcomings■ Simplistic shading■No antialiasing, motion blur, transparency

Render Caching

Pixar’s Lpics

■Production shaders& lights (RenderMan)

■Exploit programmable GPUs

■No antialiasing, transparency

■Requires extra shader-writing work■ (final) RenderMan version

+ extra caching code

■GPU preview version

[Pellacini et al. 2005]

Specializing Shaders

■Given dynamic parameters, automatically split shader code into:■ static■ dynamic

■Simple languageno control flow

■Simple shaders

[Guenter et al. 1995]

8

Bibliography [1] Andersen, Lars Ole. Self-applicable C Program

Specialization. Proceedings of the ACM SIGPLAN

Workshop on Partial Evaluation and Semantics-Based

Program Manipulation (San Francisco, California, June 12-

20, 1992). Yale University technical report

YALEU/DCS/RR-909, 1992, 54-61.

[2] Andersen, Peter Holst. Partial Evaluation Applied to Ray

Tracing. Unpublished manuscript, October 1994.

[3] Baier, Romana, Robert Glück, and Robert Zöchling. Partial

Evaluation of Numerical Programs in Fortran. Proceedings

of the ACM SIGPLAN Workshop on Partial Evaluation and

Semantics-Based Program Manipulation (Orlando, Florida,

June 25, 1994). University of Melbourne technical report

94/9, 1994, 119-132

[4] Demers, Alan J., Thomas Reps, and Tim Teitelbaum.

Incremental Evaluation for Attribute Grammars with

Application to Syntax-directed Editors. Proceedings of the

Eighth Annual ACM Symposium on Principles of

Programming Languages (Williamsburg, Virginia, January

1981), 105-116.

[5] Goad, Chris. Special Purpose Automatic Programming for

Hidden Surface Elimination. Proceedings of SIGGRAPH 82

(Boston, Massachusetts, July 26-30, 1982). In Computer

Graphics 16, 3 (July 1982), 167-178.

[6] Hanrahan, Pat. Ray Tracing Algebraic Surfaces.

Proceedings of SIGGRAPH 83 (Detroit, Michigan, July 25-

29, 1983). In Computer Graphics 17, 3 (July 1983), 83-90.

[7] Hanrahan, Pat and Jim Lawson. A Language for Shading

and Lighting Calculations. Computer Graphics 24, 4

(August 1990), 289-298.

[8] Hoover, Roger. Alphonse: Incremental Computation as a

Programming Abstraction. Proceedings of the SIGPLAN

‘92 Conference on Programming Language Design and

Implementation (San Francisco, California, June 1992),

261-272.

[9] Jones, Neil D., Carsten K. Gomard, and Peter Sestoft.

Partial Evaluation and Automatic Program Generation.

Prentice-Hall, 1993.

[10] Mogensen, Torben. The Application of Partial Evaluation to

Ray-Tracing. Master's thesis, DIKU, University of

Copenhagen, Denmark, 1986.

[11] Osgood, Nathaniel David. PARTICLE: an Automatic

Program Specialization System for Imperative and Low-

level Languages. Master's thesis, MIT, September 1993.

[12] Pugh, William and Tim Teitelbaum. Incremental

Computation Via Function Caching. Proceedings of the

Sixteenth Annual ACM Symposium on Principles of

Programming Languages (Austin, Texas, January 1989),

315-328.

[13] Ruf, Erik. Topics in Online Partial Evaluation. Ph.D.

thesis, Stanford University, April 1993. Published as

Stanford Computer Systems Laboratory technical report

CSL-TR-93-563, March 1993.

[14] Sequin, Carlo H. and Eliot K. Smyrl. Parameterized Ray

Tracing. Proceedings of SIGGRAPH 89 (Boston,

Massachusetts, July 31-August 4, 1989). In Computer

Graphics 23, 3 (July 1989), 307-314.

[15] Sundaresh, R.S. and Paul Hudak. A Theory of Incremental

Computation and Its Application. Proceedings of the

Eighteenth Annual ACM Symposium on Principles of

Programming Languages (Orlando, Florida, January 1991),

1-13.

[16] Upstill, Steve. The RenderMan Companion. Addison-

Wesley, 1989.

[17] Watkins, Christopher D., Stephen B. Coy, and Mark Finlay.

Photorealism and Ray Tracing in C. M&T Books, 1992

[18] Watt, Alan and Mark Watt. Advanced Animation and

Rendering Techniques. ACM Press, 1992.

Plate 1: Test image.

Plate 2: Image obtained by reshading image of Plate 1. This

took 12 seconds unspecialized, 0.5 seconds specialized.

8

Bibliography [1] Andersen, Lars Ole. Self-applicable C Program

Specialization. Proceedings of the ACM SIGPLAN

Workshop on Partial Evaluation and Semantics-Based

Program Manipulation (San Francisco, California, June 12-

20, 1992). Yale University technical report

YALEU/DCS/RR-909, 1992, 54-61.

[2] Andersen, Peter Holst. Partial Evaluation Applied to Ray

Tracing. Unpublished manuscript, October 1994.

[3] Baier, Romana, Robert Glück, and Robert Zöchling. Partial

Evaluation of Numerical Programs in Fortran. Proceedings

of the ACM SIGPLAN Workshop on Partial Evaluation and

Semantics-Based Program Manipulation (Orlando, Florida,

June 25, 1994). University of Melbourne technical report

94/9, 1994, 119-132

[4] Demers, Alan J., Thomas Reps, and Tim Teitelbaum.

Incremental Evaluation for Attribute Grammars with

Application to Syntax-directed Editors. Proceedings of the

Eighth Annual ACM Symposium on Principles of

Programming Languages (Williamsburg, Virginia, January

1981), 105-116.

[5] Goad, Chris. Special Purpose Automatic Programming for

Hidden Surface Elimination. Proceedings of SIGGRAPH 82

(Boston, Massachusetts, July 26-30, 1982). In Computer

Graphics 16, 3 (July 1982), 167-178.

[6] Hanrahan, Pat. Ray Tracing Algebraic Surfaces.

Proceedings of SIGGRAPH 83 (Detroit, Michigan, July 25-

29, 1983). In Computer Graphics 17, 3 (July 1983), 83-90.

[7] Hanrahan, Pat and Jim Lawson. A Language for Shading

and Lighting Calculations. Computer Graphics 24, 4

(August 1990), 289-298.

[8] Hoover, Roger. Alphonse: Incremental Computation as a

Programming Abstraction. Proceedings of the SIGPLAN

‘92 Conference on Programming Language Design and

Implementation (San Francisco, California, June 1992),

261-272.

[9] Jones, Neil D., Carsten K. Gomard, and Peter Sestoft.

Partial Evaluation and Automatic Program Generation.

Prentice-Hall, 1993.

[10] Mogensen, Torben. The Application of Partial Evaluation to

Ray-Tracing. Master's thesis, DIKU, University of

Copenhagen, Denmark, 1986.

[11] Osgood, Nathaniel David. PARTICLE: an Automatic

Program Specialization System for Imperative and Low-

level Languages. Master's thesis, MIT, September 1993.

[12] Pugh, William and Tim Teitelbaum. Incremental

Computation Via Function Caching. Proceedings of the

Sixteenth Annual ACM Symposium on Principles of

Programming Languages (Austin, Texas, January 1989),

315-328.

[13] Ruf, Erik. Topics in Online Partial Evaluation. Ph.D.

thesis, Stanford University, April 1993. Published as

Stanford Computer Systems Laboratory technical report

CSL-TR-93-563, March 1993.

[14] Sequin, Carlo H. and Eliot K. Smyrl. Parameterized Ray

Tracing. Proceedings of SIGGRAPH 89 (Boston,

Massachusetts, July 31-August 4, 1989). In Computer

Graphics 23, 3 (July 1989), 307-314.

[15] Sundaresh, R.S. and Paul Hudak. A Theory of Incremental

Computation and Its Application. Proceedings of the

Eighteenth Annual ACM Symposium on Principles of

Programming Languages (Orlando, Florida, January 1991),

1-13.

[16] Upstill, Steve. The RenderMan Companion. Addison-

Wesley, 1989.

[17] Watkins, Christopher D., Stephen B. Coy, and Mark Finlay.

Photorealism and Ray Tracing in C. M&T Books, 1992

[18] Watt, Alan and Mark Watt. Advanced Animation and

Rendering Techniques. ACM Press, 1992.

Plate 1: Test image.

Plate 2: Image obtained by reshading image of Plate 1. This

took 12 seconds unspecialized, 0.5 seconds specialized.

Precomputed Radiance Transfer

e.g. Sloan et al. 2002, Ng et al. 2003

Inappropriate for our application■ Large precomputation cost■ Largely ignore light functions■ Limitations on shading models

Precomputed Radiance Transfer for Real-Time Rendering in Dynamic, Low-Frequency Lighting Environments Peter-Pike Sloan Jan Kautz John Snyder Microsoft Research [email protected]

Max-Planck-Institut für Informatik [email protected]

Microsoft Research [email protected]

Abstract We present a new, real-time method for rendering diffuse and glossy objects in low-frequency lighting environments that cap-tures soft shadows, interreflections, and caustics. As a preprocess, a novel global transport simulator creates functions over the object’s surface representing transfer of arbitrary, low-frequency incident lighting into transferred radiance which includes global effects like shadows and interreflections from the object onto itself. At run-time, these transfer functions are applied to actual incident lighting. Dynamic, local lighting is handled by sampling it close to the object every frame; the object can also be rigidly rotated with respect to the lighting and vice versa. Lighting and transfer functions are represented using low-order spherical harmonics. This avoids aliasing and evaluates efficiently on graphics hardware by reducing the shading integral to a dot product of 9 to 25 element vectors for diffuse receivers. Glossy objects are handled using matrices rather than vectors. We further introduce functions for radiance transfer from a dynamic lighting environment through a preprocessed object to neighboring points in space. These allow soft shadows and caustics from rigidly moving objects to be cast onto arbitrary, dynamic receivers. We demonstrate real-time global lighting effects with this approach.

Keywords: Graphics Hardware, Illumination, Monte Carlo Techniques,

Rendering, Shadow Algorithms.

1. Introduction

Lighting from area sources, soft shadows, and interreflections are important effects in realistic image synthesis. Unfortunately, general methods for integrating over large-scale lighting environ-ments [8], including Monte Carlo ray tracing [7][21][25], rad-iosity [6], or multi-pass rendering that sums over multiple point light sources [17][27][36], are impractical for real-time rendering.

Real-time, realistic global illumination encounters three difficul-ties – it must model the complex, spatially-varying BRDFs of real materials (BRDF complexity), it requires integration over the hemisphere of lighting directions at each point (light integration), and it must account for bouncing/occlusion effects, like shadows, due to intervening matter along light paths from sources to receiv-ers (light transport complexity). Much research has focused on extending BRDF complexity (e.g., glossy and anisotropic reflec-tions), solving the light integration problem by representing incident lighting as a sum of directions or points. Light integra-tion thus tractably reduces to sampling an analytic or tabulated BRDF at a few points, but becomes intractable for large light sources. A second line of research samples radiance and pre-convolves it with kernels of various sizes [5][14][19][24][34]. This solves the light integration problem but ignores light trans-port complexities like shadows since the convolution assumes the incident radiance is unoccluded and unscattered. Finally, clever techniques exist to simulate more complex light transport, espe-cially shadows. Light integration becomes the problem; these techniques are impractical for very large light sources.

Our goal is to better account for light integration and light trans-port complexity in real-time. Our compromise is to focus on low-

frequency lighting environments, using a low-order spherical harmonic (SH) basis to represent such environments efficiently without aliasing. The main idea is to represent how an object scatters this light onto itself or its neighboring space.

To describe our technique, assume initially we have a convex, diffuse object lit by an infinitely distant environment map. The object’s shaded “response” to its environment can be viewed as a transfer function, mapping incoming to outgoing radiance, which in this case simply performs a cosine-weighted integral. A more complex integral captures how a concave object shadows itself, where the integrand is multiplied by an additional transport factor representing visibility along each direction.

Our approach is to precompute for a given object the expensive transport simulation required by complex transfer functions like shadowing. The resulting transfer functions are represented as a dense set of vectors or matrices over its surface. Meanwhile, incident radiance need not be precomputed. The graphics hard-ware can dynamically sample incident radiance at a number of points. Analytic models, such as skylight models [33] or simple geometries like circles, can also be used.

By representing both incident radiance and transfer functions in a linear basis (in our case, SH), we exploit the linearity of light transport to reduce the light integral to a simple dot product between their coefficient vectors (diffuse receivers) or a simple linear transform of the lighting coefficient vector through a small transfer matrix (glossy receivers). Low-frequency lighting envi-ronments require few coefficients (9-25), enabling graphics hardware to compute the result in a single pass (Figure 1, right). Unlike Monte-Carlo and multi-pass light integration methods, our run-time computation stays constant no matter how many or how big the light sources, and in fact relies on large-scale, smooth lighting to limit the number of SH coefficients necessary.

We represent complex transport effects like interreflections and caustics in the transfer function. Since these are simulated as a preprocess, only the transfer function’s basis coefficients are affected, not the run-time computation. Our approach handles both surface and volume-based geometry. With more SH coeffi-cients, we can even handle glossy (but not highly specular) receivers as well as diffuse, including interreflection. 25 coeffi-cients suffice for useful glossy effects. In addition to transfer from a rigid object to itself, called self-transfer, we generalize the technique to neighborhood-transfer from a rigid object to its neighboring space, allowing cast soft shadows, glossy reflections, and caustics on dynamic receivers, see Figure 7.

Figure 1: Precomputed, unshadowed irradiance from [34] (left) vs. our precomputed transfer (right). The right model can be rendered at 129Hz with self-shadowing and self-interreflection in any lighting environment.

Our Design Goals

1.High-performance preview■ Low-latency feedback■ Fast initial precomputation

2.Seamless integration■ Same input: RenderMan scene & shaders

■ Same output: high quality image

3.Ease of implementation & maintenance

System Overview

System Overview

RenderMan scene & shaders

System Overview


cache & preview shaders

automaticcaching

System Overview


preview imagecache & preview shaders

relighting engine(gpu)

automaticcaching

System Overview




lighting parameters

iterative preview

automaticcaching

one-time precomputation

System Overview




lighting parameters

Automaticfor real production scenes‣ specialization & translation‣ cache compression


automaticcaching

System Overview




lighting parameters


High fidelityantialiasing, motion blur, transparency‣ indirect framebuffer

automaticcaching

Automatic Caching


cache & preview shaders

automaticcaching

preview image


lighting parameters

Program Analysis

Program Analysis

mySurface(colorc){albedo=c*Texture(U,V);shade=Light(L)*BRDF(N,L);returnalbedo*shade;

}

Program Analysis


}

what part of the code depends on the lighting parameter L?

dynamic

Program Analysis


}

everything else is static

staticdynamic

Program Analysis

values at the boundary are cached for reevaluation


}

staticcache

dynamic

Program Analysis


}

Program Analysis


}

albedo

c Texture

U V

shade

Light BRDF

L N

Deep Framebuffer Generation


}


mySurfaceCache(colorc){albedo=c*Texture(U,V);cache(N);cache(albedo);

}

caching shader


albedoN

mySurfaceCache(colorc){albedo=c*Texture(U,V);cache(N);cache(albedo);

}

deep framebuffer cache

caching shader

final renderer


albedoN


caching shader


albedoN

mySurfaceDynamic(vectorL){N=lookup();albedo=lookup();shade=Light(L)*BRDF(N,L);returnalbedo*shade;

}preview shader


caching shader


albedoN

preview shader


rendered imageshade

caching shader

Automatic Caching

Automatic Caching

RenderMan shaders

scene preprocessorRenderManscene

Automatic Caching

RenderMan shaders

scene preprocessor

program analysis

RenderManscene

Automatic Caching

RenderMan shaders

scene preprocessor

program analysis

RenderManscene

caching shaders

Automatic Caching

RenderMan shaders

scene preprocessor

final renderer

program analysis

RenderManscene


PN

x1x2

caching shaders

Automatic Caching

RenderMan shaders

scene preprocessor

dynamicpreview shaders

final renderer

program analysis

RenderManscene


PN

x1x2

caching shaders

Automatic Caching

RenderMan shaders

scene preprocessor


final renderer

program analysis

RenderManscene


conservative

many cached terms

large caches

(hundreds)

(gigabytes)

program analysis is

generates

PN

x1x2

caching shaders

challenge: cache size

PN

x1x2

Cache Compression

scene preprocessor

final renderer

program analysis

Remove redundant values after caching

RenderMan shaders


RenderManscene


caching shaders

PN

x1x2

Cache Compression

scene preprocessor

final renderer

program analysis


RenderMan shaders


RenderManscene


cache compression

PN

caching shaders

PN

x1x2

Cache Compression

scene preprocessor

final renderer

program analysis


→ 5x compressionRenderMan shaders


RenderManscene


cache compression

PN

caching shaders

System Overview

scene preprocessor

final renderer

program analysis

cache comp.

RenderMan shaders


RenderManscene


PN

caching shaders

scene preprocessor

final renderer

program analysis

RenderMan shaders

RenderManscene

cache compr.

caching shaders

System Overview

scene preprocessor

final renderer

program analysis

cache comp.

RenderMan shaders


RenderManscene


PN

caching shaders

System Overview

preview image


scene preprocessor

final renderer

program analysis

cache comp.

RenderMan shaders


RenderManscene


PN

caching shaders

lighting parameters

System Overview

preview image


scene preprocessor

final renderer

program analysis

cache comp.

RenderMan shaders


RenderManscene


antialiasing?transparency?

PN

caching shaders

lighting parameters

Classical Deep Framebuffer

A

B


PN

x1

x2

A

B

cache

shade


rendered image

Cache one sample per-pixelShade cache values to render image


PN

x1

x2

A

B

cache

shade

How can we do antialiasing?


rendered image

PN

x1

x2


A

B

cache

shade

How can we do antialiasing?transparency?

supersample image


A

B

cache

shade


PN

x3

x4supersample cache

supersample shading


A

B

cache

shade


PN

x3

x4

...?

...?

Our Indirect Framebuffer

■Decouple shading from visibility■ only supersample visibility

‣Do what RenderMan does

■Compress samplesbased on static visibility

RenderMan / REYES

A

B

show *filtering* pixel color?

RenderMan / REYES

b1

A

B

b2

a1


dice into micropolygons

RenderMan / REYES

b1

A

B

b2

a1


shade micropolygons

RenderMan / REYES

b1

A

B

b2

a1


rasterize micropolygons

RenderMan / REYES

b1

A

B

b2

a1


RenderMan / REYES

b1

A

B

b2

a1

1 2

3 4

a1

1

a1

3

a1

4

b2

2


a1pixel = +b2+a1+a1

RenderMan / REYES

b1

A

B

b2

a1

1 2

3 4

a1

1

a1

3

a1

4

b2

2


a1pixel =4

+b2+a1+a1

RenderMan / REYES

b1

A

B

b2

a1

1 2

3 4

a1

1

a1

3

a1

4

b2

2


a1pixel =4

+b2+a1+a1 = 0.75*a1+0.25*b2

RenderMan / REYES

b1

A

B

b2

a1

1 2

3 4

a1

1

a1

3

a1

4

b2

2


pixel =?

b1

RenderMan / REYES

a1

A

B

b2

pixel =?

b1

RenderMan / REYES

a1

A

B a1

α=0.3b1

α=1.0

1

0.3*a1+0.7*b1

b2

pixel =?

1

b1

RenderMan / REYES

a1

A

B a1

α=0.3b1

α=1.0

1

0.3*a1+0.7*b1

b2

α=1.0

2

1.0*b2

b2

pixel =?

1 2

b1

RenderMan / REYES

a1

A

B a1

α=0.3b1

α=1.0

1

0.3*a1+0.7*b1

a1

α=0.3

3

0.3*a1

a1

α=0.3b2

α=1.0

4

0.3*a1+0.7*b1

b2

α=1.0

2

1.0*b2

b2

pixel =?

1 2

3 4

b1

RenderMan / REYES

a1

A

B a1

α=0.3b1

α=1.0

1

0.3*a1+0.7*b1

a1

α=0.3

3

0.3*a1

a1

α=0.3b2

α=1.0

4

0.3*a1+0.7*b1

b2

α=1.0

2

1.0*b2

b2

pixel = 0.225*a1+0.35*b1+0.25*b2

1 2

3 4

Indirect Framebuffer

Indirect Framebufferb1

b2a1


Px2

PP

x3

Nx1

x2

x3

∅ x4

b2b1a1

x4

b1b2a1

no longer image space(per-micropolygon)

deepbuffer


shadingsamples

Px2

PP

x3

Nx1

x2

x3

∅ x4

b2b1a1

x4

b1b2a1

shade

deepbuffer

shaded like a conventional deep-framebuffer


shadingsamples

Px2

PP

x3

Nx1

x2

x3

∅ x4

b2b1a1

x4

b1b2a1

shade

indirect framebufferdeepbuffer


shadingsamples

Px2

PP

x3

Nx1

x2

x3

∅ x4

b2b1a1

x40.225 0.35 0.25

b1b2a1

shade


densely stored in vertex array, on GPU


shadingsamples

Px2

PP

x3

Nx1

x2

x3

∅ x4

b2b1a1

x40.225 0.35 0.25

finalpixel

b1b2a1

shade

blend


4 subpixel samples, 2 transparent layersonly 3 unique micropolygons


shadingsamples

Px2

PP

x3

Nx1

x2

x3

∅ x4

b2b1a1

x40.225 0.35 0.25

finalpixel

b1b2a1

shade

blend


all contributions linearized into a single weight

4 subpixel samples, 2 transparent layersonly 3 unique micropolygons

shadingsamples

Px2

PP

x3

Nx1

x2

x3

∅ x4

b2b1a1

x40.242 0.331 0.245

finalpixel

b1b2a1

shade

blend

indirect framebuffer

More samples,Same cost

deepbuffer

deepbuffer

shadingsamples

Px2

PP

x3

Nx1

x2

x3

∅ x4

b2b1a1

x4

finalpixel

b1b2a1

shade

blend

More samples,Same cost

0.242 0.331 0.245

indirect framebuffer

Indirect Framebuffer Resultsantialiasingmotion blurtransparencyidentical to RenderMan

Indirect Framebuffer Resultsantialiasingmotion blurtransparencyidentical to RenderMan

RenderMan45M micropolygons

60M subpixel samples

brute-force>100M samples

Indirect framebuffer 10M deep fb+15M indirect fb

720x389, 64x supersampling

System Architecture

System Architecture

RenderMan shaders

scene preprocessorRenderManscene

System Architecture

RenderMan shaders

scene preprocessor

program analysis

RenderManscene

System Architecture

RenderMan shaders

scene preprocessor

preview shaders

program analysis

RenderManscene

caching shaders

System Architecture

RenderMan shaders

scene preprocessor

preview shaders

final renderer

program analysis

RenderManscene

caching shaders

System Architecture

RenderMan shaders

scene preprocessor

preview shaders

final renderer

program analysis

cache compr.

RenderManscene

PN

x1x2

caching shaders

deep fb indirect fb

System Architecture

RenderMan shaders

relighting engine (GPU)scene preprocessor

preview shaders

final renderer

program analysis

cache compr.

RenderManscene

PN

x1x2

caching shaders

deep fb indirect fb

System Architecture

RenderMan shaders


preview shaders

final renderer

program analysis

cache compr.

RenderManscene

PN

x1x2

caching shaders shade

deep fb indirect fb

rendered image

System Architecture

RenderMan shaders


preview shaders

final renderer

program analysis

cache compr.

RenderManscene

PN

x1x2


deep fb indirect fb

blend

rendered image

System Architecture

RenderMan shaders


preview shaders

final renderer

program analysis

lightingparameters

cache compr.

RenderManscene

PN

x1x2


deep fb indirect fb

blend

iterative preview one-time precomputation

Additional Features

■Shadows

■Subsurface Scattering

■Performanceenhancement■ Progressive Refinement

■ Light Caching

■ Tiling…

Results

Lightspeed720x389

initial feedback: 0.05 secfull refinement: 0.7 sec

offline render: 5 mins

Results

LightspeedRenderMan720x389



Results

Results

914x38913x13 antialiasing42 lights



caching: 16 mins

Results

Lightspeed

RenderMan914x38913x13 antialiasing42 lights



caching: 16 mins

Results

Limitations

■GPU programming model■Dynamic calls to external C code■Complex data structures■GPU limits (bandwidth, memory, registers)

■ Fully-accurate dynamic ray tracing

■Unbounded dynamic loops

■Additional features not yet implemented

■ Indirect diffuse

■Deep shadows

■Non-linear lights

Discussion

■Automatic and manual specialization (Lpics) both have advantages■Manual specialization allows hand optimization■Compiler requires up-front R&D, never perfect

(especially on the GPU)

■ Saves significant time in production■ Some material parameters are editable

■Cache compression is key to practical automatic specializationmuch simpler than fancy static analysis

■ Indirect Framebuffer is powerful, scalable

Summary

■ Interactive lighting previewmilliseconds instead of hours

■Automatic caching for our production scenes■ Program analysis■Cache compression

■ Indirect framebuffer■ Efficient antialiasing, motion blur, transparency■ Progressive refinement

■ In use on current productions

Acknowledgments

Inception: Pat Hanrahan, Ujval Kapasi

Compilers: Alex Aiken, John Kodumal

Tippett: Aaron Luk, Davey Wentworth

ILM: Alan Trombla, Ed Hanway, Dan Goldman, Steve Sullivan, Paul Churchill

Images: Michael Bay, Dan Piponi

Money: NSF, NVIDIA, MSR, Sloan & Ford fellowships

Summary

■ Interactive lighting previewmilliseconds instead of hours

■Automatic caching for our production scenes■ Program analysis■Cache compression

■ Indirect framebuffer■ Efficient antialiasing, motion blur, transparency■ Progressive refinement

■ In use on current productions

EXTRAS

Cache Compression

Remove redundant values after caching■ non-varying

same for many pixels

■ non-uniquesame within a pixel

→ 4-5x compression

varying

unique


Cache Compression

shader dynamic(static analysis)

varying unique(compressed)

generic surface 402 145 97

metallic paint 450 150 97

Visibility Compression

RenderManIndirect

Framebuffer

scene res. samples shade subpix shade indirect

robot 914x389 13x13 2.1M 32M 633k 1.6M

robot (blur)

720x306 13x13 1.5M 21M 467k 3.8M

pirate 640x376 4x4 2.5M 2.3M 327k 716k

hairs 720x389 8x8 43M 58M 11M 17M

Lightspeed SIGGRAPH talk

Technology

Transcript of Lightspeed SIGGRAPH talk