Practical Parallel Rendering

Practical Parallel Rendering Practical Parallel Rendering Edited by Alan Chalm ers Timothy Davis Erik Reinhard A K ...

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Practical Parallel Rendering

Practical Parallel Rendering

Edited by

Alan Chalm ers Timothy Davis Erik Reinhard

A K Peters Natick, Massachusetts

Editorial, Sales, and Customer Service Office A K Peters, Ltd. 63 South Avenue Natick, MA 01760 www.akpeters.com Copyright © 2002 by A K Peters, Ltd. All rights reserved. No part of the material protected by this copyright notice may be reproduced or utilized in any form , electronic o r mechanical, inc luding photocop ying, recording, or by an y information storage and retrieval system, without written permission from the copyright owner.

Library of Congress Cataloging-in-Publication Data Practical parallel rendering / edited by Alan Chalmers, Timothy Davis, Erik Reinhard. p. cm. Includes bibliographical references and index. ISBN 1-56881-179-9 1. Parallel processing (Electronic computers) 2. Electronic data processing-Distributed processing. I Chalmers, Alan II. Davis, Timothy, 1965- III. Reinhard, Erik, 1968- IV. Title. QA76.58 .C44 2002 004'.35-dc21 2002070381

Printed in Canada 06 05 04 03 02

10 9 8 7 6 5 4 3 2 1

Contents

I

Preface

xi

Parallel Rendering

1

1 Introduction to Parallel Processing 1.1

1.2 1.3

1.4

Concepts....................................................................................... 1.1.1 Dependencies .............................................................. 1.1.2 Scalability......................................................................... 1.1.3 Control.............................................................................. Classification of Parallel Systems .............................................. 1.2.1 Parallel versus Distributed Systems.................................. The Relationship of Tasks and Data.......................................... 1.3.1 Inherent Difficulties ..................................................... 1.3.2 Tasks ............................................................................ 1.3.3 Data .................................................................................. Evaluating Parallel Implementations........................................ 1.4.1 Realization Penalties ................................................... 1.4.2 Performance Metrics ........................................................ 1.4.3 Efficiency .........................................................................

2 Task Scheduling and Data Management 2.1 Problem Decomposition............................................................... 2.1.1 Algorithmic Decomposition ............................................. 2.1.2 Domain Decomposition ................................................ 2.1.3 Abstract Definition of a Task ........................................... 2.1.4 System Architecture .........................................................

V

3 4 5 6 7 7 13 14 15 16 16 17 18 20 25 31 31 32 32 34 34

vi

Contents

2.2

2.3

2.4

2.5

Computational Models .......................................................... 2.2.1 Data Driven Model ....................................................... 2.2.2 Demand Driven Model ..................................................... 2.2.3 Hybrid Computational Model ...................................... Task Management .................................................................. 2.3.1 Task Definition and Granularity ................................... 2.3.2 Task Distribution and Control ...................................... 2.3.3 Algorithmic Dependencies .......................................... Task Scheduling Strategies ..................................................... 2.4.1 Data Driven Task Management Strategies ....................... 2.4.2 Demand Driven Task Management Strategies .... 2.4.3 Task Manager Process...................................................... 2.4.4 Distributed Task Management ...................................... 2.4.5 Preferred Bias Task Allocation......................................... Data Management .................................................................. 2.5.1 World Model of the Data: No Data Management Required ....................................... 2.5.2 Virtual Shared Memory.................................................... 2.5.3 The Data Manager ............................................................ 2.5.4 Consistency ................................................................. 2.5.5 Minimizing the Impact of Remote Data Requests . . 2.5.6 Data Management for Multistage Problems .....................

3 Parallel Global Illumination Algorithms 3.1 3.2 3.3 3.4

3.5

3.6

3.7

Rendering..................................................................................... Parallel Processing .................................................................. Ray Tracing ................................................................................. Spatial Subdivisions .................................................................... 3.4.1 Parallel Ray Tracing ......................................................... 3.4.2 Demand Driven Ray Tracing............................................ 3.4.3 Data Parallel Ray Tracing ................................................ 3.4.4 Hybrid Scheduling............................................................ Radiosity ...................................................................................... 3.5.1 Form Factors..................................................................... 3.5.2 Parallel Radiosity ......................................................... Full Matrix Radiosity.................................................................. 3.6.1 Setting Up the Matrix of Form Factors ............................ 3.6.2 Solving the Matrix of Form Factors ................................. 3.6.3 Group Iterative Methods .............................................. Progressive Refinement .......................................................... 3.7.1 Parallel Shooting ...............................................................

36 36 41 46 46 46 48 49 53 53 54 59 62 64 65 66 67 69 76 80 85 89 90 92 94 96 99 99 104 107 109 110 Ill 112 113 115 115 116 118

Contents

4

3.8

Hierarchical Radiosity ................................................................ 3.8.1 Parallel Hierarchical Radiosity ....................................... 3.9 Particle Tracing........................................................................... 3.9.1 Parallel Particle Tracing ................................................... 3.9.2 Density Estimation ........................................................... 3.10 Data Distribution and Data Locality ......................................... 3.10.1 Data Distribution .......................................................... 3.10.2 Visibility Preprocessing ................................................... 3.10.3 Environment Mapping...................................................... 3.10.4 Geometric Simplification ................................................. 3.10.5 Directional Caching ...................................................... 3.10.6 Reordering Computations................................................. 3.11 Discussion.....................................................................................

120 121 122 123 124 125 126 127 128 128 130 130 131

Overview of Parallel Graphics Hardware

133

4.1 4.2

133 136 136 139 142 146 149 151

4.3 5

vii

Pipelining ..................................................................................... Parallelism in Graphics Cards................................................... 4.2.1 3DLABS Products............................................................ 4.2.2 Hewlett-Packard Products ................................................ 4.2.3 SGI Products (Silicon Graphics, Inc.) .......................... 4.2.4 UNC Products .................................................................. 4.2.5 Pomegranate Graphics Chip ............................................. Conclusion ...................................................................................

Coherence in Ray Tracing 5.1

5.2

Scene Analysis ............................................................................. 5.1.1 Distribution of Data Accesses .......................................... 5.1.2 Temporal Characteristics ............................................... 5.1.3 Temporal Behaviour per Ray Type .................................. 5.1.4 Conclusions ...................................................................... Animation Analysis..................................................................... 5.2.1 Background ...................................................................... 5.2.2 Related Work.................................................................... 5.2.3 Frame Coherence Algorithm ............................................ 5.2.4 Parallel Frame Coherence Algorithm ............................... 5.2.5 Results .......................................................................... 5.2.6 Summary ..........................................................................

153 154 155 158 162 164 165 166 167 169 174 176 184

viii

II

Contents

Case Studies

6 Interactive Ray Tracing on a Supercomputer 6.1

6.2

6.3 6.4

System Architecture.................................................................... 6.1.1 Conventional Operation.................................................... 6.1.2 Frameless Rendering ........................................................ 6.1.3 Performance .................................................................. Ray Tracing for Volume Visualization...................................... 6.2.1 Background ...................................................................... 6.2.2 Traversal Optimizations ................................................... 6.2.3 Algorithms........................................................................ 6.2.4 Results .......................................................................... 6.2.5 Discussion ........................................................................ Ray Tracing for Terrain Visualization...................................... Conclusions..................................................................................

7 Interactive Ray Tracing on PCs 7.1 Introduction ............................................................................. 7.1.1 Previous Work.................................................................. 7.2 An Optimized Ray Tracing Implementation ............................ 7.2.1 Code Complexity.............................................................. 7.2.2 Caching............................................................................. 7.2.3 Coherence through Packets of Rays ................................. 7.2.4 Parallelism through SIMD Extensions ............................. 7.3 Ray Triangle Intersection Computation ................................... 7.3.1 Optimized Barycentric Coordinate Test ........................... 7.3.2 Evaluating Instruction Level Parallelism.......................... 7.3.3 SIMD Barycentric Coordinate Test.................................. 7.4 BSP Traversal.............................................................................. 7.4.1 Traversal Algorithm ......................................................... 7.4.2 Memory Layout for Better Caching ................................. 7.4.3 Traversal Overhead .......................................................... 7.5 SIMD Phong Shading ............................................................. 7.6 Performance of the Ray Tracing Engine................................... 7.6.1 Comparison to Other Ray Tracers .................................... 7.6.2 Reflection and Shadow Rays ........................................ 7.6.3 Comparison with Rasterization Hardware........................ 7.7 Interactive Ray Tracing on PC Clusters ................................... 7.7.1 Overview...........................................................................

185 187 188 189 192 193 194 195 197 201 205 211 214 215 21*7 217 220 221 221 222 223 223 223 223 224 224 226 226 228 229 229 231 231 233 234 236 238

Contents

ix

7.8 Distributed Data Management................................................... 7.8.1 Explicit Data Management ............................................... 7.8.2 Preprocessing ................................................................... 7.9 Load Balancing............................................................................ 7.10 Implementation ....................................................................... 7.11 Results .......................................................................................... 7.12 Conclusions.................................................................................. 8 The "Kilauea" Massively Parallel Ray Tracer 8.1 8.2 8.3

8.4 8.5 8.6

8.7

8.8 8.9

What Is the Kilauea Project? ................................................. Basic Idea..................................................................................... System Design.............................................................................. 8.3.1 Hardware Environment ................................................ 8.3.2 Pthreads ........................................................................ 8.3.3 Message Passing............................................................... 8.3.4 Front-End Process ............................................................ 8.3.5 Launching Kilauea ........................................................... 8.3.6 Single Executable Binary ................................................. 8.3.7 Multiframe Rendering ...................................................... 8.3.8 Global Illumination Renderer........................................... The ShotData File Format ...................................................... Parallel Ray Tracing................................................................... Implementation ....................................................................... 8.6.1 Low-Level Data Structure ................................................ 8.6.2 MPI (Message Passing Interface) Layer ....................... 8.6.3 Tel Command Interface.................................................... 8.6.4 Rank and Task.................................................................. 8.6.5 Details of Ray Tracing ..................................................... 8.6.6 Shading Computation ....................................................... 8.6.7 Photon Map Method......................................................... 8.6.8 Things to Note in Shading Computation .......................... 8.6.9 Development in General................................................... Rendering Results ....................................................................... 8.7.1 Sample 1: Quatro .......................................................... 8.7.2 Sample 2: Jeep.................................................................. 8.7.3 Sample 3: Jeep 8............................................................... 8.7.4 Consideration of Rendering Results................................. Conclusion ................................................................................... Future Plans and Tasks ..........................................................

239 239 241 241 242 243 246 249 249 250 251 251 252 252 253 253 254 254 255 256 261 268 268 277 279 281 288 291 306 310 314 316 316 319 321 322 323 325

x

Contents

9 Parallel Ray Tracing on a Chip 329 9.1 The Smart Memories Chip......................................................... 329 9.2 The SHARP Ray Tracer............................................................. 331 9.3 Simulation Results ................................................................... 333 9.3.1 Caching............................................................................. 334 9.3.2 Estimated Performance..................................................... 335 9.4 Conclusions.................................................................................. 336 Bibliography

337

Index

363

Author Biographies

369

Preface

The eve r i ncreasing c omputational dem ands ass ociated with re ndering has meant th at p arallel rend ering is alm ost as ol d as re ndering i tself. However, the fu ll po tential p arallel pro cessing has to offer of producing won derful images in reasonable tim es h as always see med to allud e tho se striv ing for this "holy grail." While p arallel p rocessing on a low nu mber of processors is relatively straightforward, the challenge com es when co nfronting an i mplementation on a l arge sy stem. Here t he ove rheads as sociated with the processors working t ogether c an ra pidly dominate and l ead t o t he frustration of a s olution time o f more than th at which was ach ievable on a single process or. And yet it is p recisely th ese larg er syst ems which offer th e co mputational p erformance we seek. The ai m of t his b ook i s t o de scribe t he pr oblems associ ated wi th parallel renderi ng, pr ovide a methodology as t o h ow t hese pr oblems can be minimized an d dem onstrate ho w, with ca re, i t i s i ndeed p ossible t o achi eve efficient parallel rendering. The book is stru ctured in to two parts. The first part is intended t o pro vide t extbook m aterial t hat i ntroduces generic parallel pr ocessing i ssues i n Chapters 1 a nd 2. With t his bac kground k nowledge, t he reade r i s t hen introduced to h igh-end graphics algo rithms su ch as ray tracin g, radiosity and particle tracing. T he s pecifics of these algorithms and their i mplications f or parallel processi ng are di scussed i n C hapter 3, while C hapter 4 deals wi th rec ent dev elopments i n har dware. F or m any of t hese al gorithms it tu rns ou t th at th e p roper ex ploitation o f co herence is essen tial. Fo r th is reason, a n in-dept h analysis of cohe rence for single im ages as well as im age sequences is presented in Chapter 5. In t he sec ond part of t his book, a number of case st udies are presented. Each case stud y u ses p arallelism to sp eed up ray tracing , but in t he process they all take very different approaches to solving the problems faced in par-

xi

Xll

Preface

allel ren dering. In Ch apter 6 p arallel ray tracin g on larg e sh ared m emory computers is sh own to p roduce in teractive fram e rates fo r d ata-sets co ntaining ten s of m illions o f quadrilaterals at scr een reso lutions o f 102 42 pi xels. A second case st udy sho ws th at clu sters of PC's can also be effectiv ely utilized to re nder v ery l arge m odels. C hapter 7 demonstrates t hat by very ca refully exploiting the caching struc ture of m odern PCs, which effectively am ounts to l everaging as m uch c oherence as possible, networks o f PC s ca n render models co ntaining m illions of t riangles at in teractive rates. Th e th ird case study i n C hapter 8 di scusses t he Kilauea pa rallel ren dering e ngine, which was used t o cr eate th e f ilm "Fin al Fan tasy". Th e last ch apter of th is b ook proposes t o i mplement ray t racing i n hardware an d as suc h t akes a ve ry different approach to parallel rendering.

Acknowledgements This b ook has evol ved o ver m any y ears. A number of t he c oncepts de scribed i n C hapter 2 were first in troduced in lecture notes at th e Un iversity of B ristol and later app eared in A.G. C halmers an d J.P. Tid mus, Practical Parallel Processing: An Introduction to Problem Solving in Parallel. International Thomson Computer Press, 1996. In 1998 we gave a co urse on paral lel ren dering at SIG GRAPH an d t hings just sn owballed fro m th ere. I wo uld firstly lik e to th ank all th e au thors wh o have con tributed to th is book. Hopefully our co mbined exp erience will h elp you get to grips with practical parallel rendering. I would also lik e to th ank th e Ren dering and Parallel Graph ics & Visualization co mmunities arou nd th e world for pro viding such a stim ulating environment in w hich to wo rk. I would enco urage an yone w ho h asn't alr eady done so , to atten d on e of the Eur ographics-ACM SIGG RAPH Workshops in these fields; they are inspiring. I have b een ex tremely lu cky to h ave b een ab le to in teract and share a beer or t hree wi th so m any wo nderful pe ople o ver t he y ears, al l of wh om have hel ped m e formulate my ideas: the ACM SI GGRAPH Exec utive Com mittee an d th e wid er ACM SIGGRAPH and Eu rographics co mmunities, especially Bo nnie Mitch ell, Ju dy Brown, Steve Cunn ingham, Leo Hourvitz, Scott Lan g, Erica Jo hnson, Na n Sc haller, G reg Ward and David Arnold to m ention on ly a v ery few; m y co lleagues and friends at th e University of B ristol, in p articular C olin Dalton, Neill Ca mpbell an d Maj id Mirm ehdi and all my cu rrent an d fo rmer PhD stud ents. Th e list cou ld go on. Finally, t hank y ou t o my fam ily and esp ecially R hona and M aya fo r t heir love and support. Alan Chalmers

Preface

xiii

I w ish to ackn owledge m y ad visor, Dr. Ed ward W . D avis, at North Carolina State Univ ersity, fo r his h elp an d guidance, a s wel l as my fam ily for their continued encouragement and support. Timothy A. Davis Several peo ple have c ontributed t o t his book i n b oth material and im material way s. T hese i nclude Chuck Hansen an d Pete S hirley f or giving m e the f reedom to pursue m y own i nterests. I'm very g rateful t o t hem as wel l as Mik e Stark , Bill Martin , Helen Hu, Margarita Bratk ova, Kristi Po tter, Bruce a nd Amy Gooc h an d m any ot hers fo r m aking living i n Utah an al most norm al experience. T hey've al so m anaged t o p ut up wi th m e fo r t wo years. Ho w co ol is th at? Finally, I wou ld lik e to than k all au thors wh o contributed their p recious ti me an d d elivered th e con tent th at I b elieve makes this book both useful and beautiful. Erik Reinhard

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Principal Data Items

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PE 1

PE 2

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PDIs for PE1

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Individual task computation times

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Principal data item specified by the task

Additional data items required

Stage 1 of algorithm Stage 1 Partial result = Stage 2 Principal data item

Additional data items required Stage 2 of algorithm

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Processing Elements PE

PE 2

1

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PE n

demands for tasks

task supply Work supplier

id PDIs ADIs

id PDIs ADIs

id PDIs ADIs id PDIs ADIs id PDIs ADIs id PDIs ADIs

id PDIs ADIs id PDIs ADIs

id PDIs ADIs

id PDIs ADIs

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SC

PE 1

PE 2

Key: SC - System Controller AP - Application Process TR - Task Router RR - Result Router

PE n

TR

AP

RR

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System Controller Tasks

PE 1

PE 2 Initial state: both APs demand work

Results Tasks

First task is loaded from SC

Results Tasks

Second task is loaded from SC

Results Tasks T I

Results

M

Tasks

E

Third task is loaded from SC

Processor farm fully loaded

Results Tasks

First result is produced

Results Tasks

AP demands next task

Results Tasks Results

Returning result causes new task to enter the farm

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Processing Elements PE 1

PE 2

PE 3 task supply

Demand for tasks Task Supplier

task ids

"Pool" of available tasks 1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

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18

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Next: The AP at PE 2 needs data item y. The DM of PE 2 obtains a copy of y from PE1.

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Finally: PE1 updates the value of y. The copy being held by the DM on PE 2 is now stale. PE 1 and PE 2 have an inconsistent view on y.

AP

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Next data item for AP

local cache id data item id data item id data item id data item local cache treated as a circular buffer

Latest prefeched data item

id id id

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VR 8t$BtI sAB% tI$t {st A I{B8}BRI $tB bB PZt{$Btsj RsR s{Y A$t s }$}j$t BP R%sj YsIbs RsR qB R}I Z} tI$t $ $R {B88Bt B ZR R%sj peR stI i=R bB,$t $t }sT sjjj >d 1(dH yt Bjts sj >dH s {jsRR$h{s$Bt BP Y }ssjjj tI$t sjB$Y8R $R 8sIU RBThR RBT8$IIj stI RBTjsR qY$R {jsRR$h{s$Bt $R AsRI Bt bY $t Y s}Y${R }$}j$t }$8$$%R s I$RT $AZI B% 8Zj$}j }B{RR$t Zt$R yt RBThR RkR8R BA`{R s I$R$AZI IZ$t B8k }B{RR$t 7BT8$IIj sjB$Y8R I$R$AT Z }$8$$%R $t Y 8$IIj BP Y s}Y${R }$}j$t Abt B8k }B{RR$t stI sR$9s$Bt bY$j $t RBTjsR }B{RR$t RB$t B{{ZR sP sR$9s$Bt yt s}Y${R YsIbs B8k }B{RR$t $R }ssjjj$9I Ak sA$s$jk sRR$t$t s{Y pe s RZAR BP Y BA`{ }$8$$%R $t Y R{t isR$9sT $Bt $R }ssjjj$9I Ak sRR$t$t s{Y i= s }B$Bt BP Y $8s wR{stTj$tR $tjs%I RZAR BP R{stTj$tR $jR {D qY BA`{R 8ZR A RBI PB8 BA`{ R}s{ B $8s R}s{ BR BP Y }ssjjj tI$t RkR8R s YPB RBT8$IIj yt Y PBjjBb$t RB8 -s8}jR BP YTI$8tR$Btsj s}Y${R {sIR s }RtI

'/$%6 3URGXFWV

G$jI{s s}Y${R {Y$}TR PB8 n*NV 7 >d1H qY G$jI{s Ps8$jk BP YTI$8tR$Btsj s}Y${R s{{jsBR bY${Y $R AsRI Bt G$jI{s:R _ssT 7{sj s{Y${Z Z$j$9R Y G$jI{s YTI$8tR$Btsj s}Y${R {Y$}TR y $R Y hR Zjk R{sjsAj YTI$8tR$Btsj s}Y${R s{Y${Z PB G$tT IBbR Wq !t 8s`B sR}{ BP Y s{Y${Z $R Y -8jk Y$Y j%j

3DUDOOHOLVP LQ *UDSKLFV &DUGV

AGP/PCI DirectBurst Memory Bus Interface ASIC

Frame Buffer Memory Geometry Accelerator ASIC

Rasterization Engine ASIC

Monitor

Wildcard 3D graphics chip-set Wildcard 3D graphics accelerator single pipeline

Texture Memory

)LJXUH G$jI{s _ss7{sj s{Y${Z PB8 n*NV 7 >d1H

BP $ts$Bt Ys YsR At s{Y$%I s Y {Y$} j%j bY${Y RZjR $t PsR 8B s&BIsAj YTI$8tR$Btsj s}Y${R Ys {st s{{js stk YTI$8tR$Btsj s}}j${s$Bt w3$Z ;nD qY PBjjBb$t IR{$}$Bt BP Y G$jI{s:R s{Y${Z $R s,t PB8 >d1H qY G$jI{s YTI$8tR$Btsj s}Y${R {Y$}TR PsZR Y {ZRB8 V7y] I%${R bY${Y s R}{$h{sjjk IR$tI B }B%$I B}$8sj }PBT 8st{ PB YTI$8tR$Btsj s}Y${R s}}j${s$BtRU q

ZR ytPs{U V R$tj {Y$} Z$j$9$t G$jI{s:R *${ ZRq {YT tBjBk $tPs{R Y YTI$8tR$Btsj s}Y${R RZARkR8 B Y YBR RkR8 %$s $Y Vp_ B _]y AZRRR

q pB8k V{{jsBU V R$tjT{Y$} B8k s{{jsB }B%$IR n1 p3N!_7 wn1 A$jj$Bt 4Bs$tT}B$t B}s$BtR } R{BtID q isR$9s$Bt et$tU V R$tj {Y$} }PB8R $stj RZ} -Z }B{RR$t stI sjj Y }$-j B}s$BtR $t%Bj%I $t sR$9s$Bt yt sII$$Bt B tZ8BZR BY PZt{$BtR Y$R I%${ sjRB {Bts$tR %$IB jBB,Z} sAjR stI I$$sj B stsjB {Bt%R w*V]RD RB Y BZ}Z PB8 Y$R {Y$} {st A ZRI B I${jk I$% Y 8Bt$B VjRB tB Ys Y Ps8 AZ& 88Bk $R I$R$t{ PB8 Y -Z 88Bk 7B8 YTI$8tR$Btsj s}Y${R RZARkR8R ZR s Zt$hI 88T Bk RZ{Z bY${Y 8stR Ys Y Rs8 }YkR${sj 88Bk $R ZRI B RsT $RPk ABY Ps8 AZ& stI -Z JZ$8tR !t }BAj8 b$Y Y$R R{Y8 $R Ys $P Y RkR8 $R Z}jBsI$t B IBbtjBsI$t -ZR Yt $ {sttB A s{{RR$t Y Ps8 AZ& s Y Rs8 $8 RjBb$t Y s}YT ${R YBZY}Z k {B8}s$RBt Y sR$9s$Bt t$t $t Y G$jI{s

2YHUYLHZ RI 3DUDOOHO *UDSKLFV +DUGZDUH

YTI$8tR$Btsj s}Y${R {Y$}TR 8}jBkR b$I $tI}tIt AZRRR PB Y Ps8 AZ& stI Y -Z 88Bk bY${Y R$t$h{stjk $t{sRR Y }PB8st{ BP Y RkR8 qk}${sj YTI$8tR$Btsj s}Y${R s{Y${ZR s AsRI Bt Y ZR BP s R$tj YTI$8tR$Btsj s}Y${R }$}j$t qY$R }$}j$t s,R Iss PB8 s YTI$8tR$Btsj s}Y${R s}}j${s$Bt stI I$R}jskR Ys Iss Bt Y R{t V ,k PsZ BP G$jI{s:R _ss7{sj s{Y${Z $R $R -T 8jk Y$Y j%j BP }ssjjj$R8 qY$R sjjBbR Y }Bb BP 8Zj$}j YT I$8tR$Btsj s}Y${R }$}j$tR B A {B8A$tI bY${Y 8stR Ys Y sR, BP Isb$t st $8s $R R}j$ Abt }$}j$tR stI s{Y }$}j$t }B{RRR Btjk s }B$Bt BP Y s}}j${s$Bt:R Iss w3$ZR ;; stI ;xD =R$t 8Zj$}j }$}j$tR B I$% s R$tj I$R}jsk $t Y$R 8stt RZjR $t s j$tsjk R{sjI }PB8st{ $t{sR qYs $R bB }$}j$tR }B%$I 1Y }PB8st{ stI PBZ }$}j$tR }B%$I ;- Y }PB8st{ BP s R$tj }$}j$t y $R $8}Bst B tB Ys Y G$jI{s s}Y${R I$% stI YsIbs YstIj Y$R {s}sA$j$k $ $R Bsjjk stR}st B Y s}}j${s$Bt stI Y ZR yt sII$$Bt B ZR$t 8Zj$}j }$}j$tR B I$% s R$tj I$R}jsk G$jIT {s:R _ss7{sj s{Y${Z sjRB sjjBbR s{Y }$}j$t B I$% $R Bbt I$RT }jsk es{Y R{t {st I$R}jsk s Zt$JZ $8s $t{jZI$t 8Zj$}j %$bR PB8 Y Rs8 s}}j${s$Bt B PB8 I$&t s}}j${s$BtR es{Y sR$9s$Bt t$t YsR $R Bbt Ps8 AZ& stI -Z 88T Bk 3ZY8B s{Y BP Y G$jI{s sR$9s$Bt t$tR $R {s}sAj BP RZ}}B$t Z} B E; BP Ps8 AZ& bY${Y JZsR B s Bsj Ps8 AZ& BP Z} B 1xE Bt s JZsI }$}j$t RkR8 7$8$jsjk Y G$jI{s YTI$8tR$Btsj s}Y${R {Y$}TR {st RZ}}B Z} B 1xE BP -Z 88Bk } sR$9s$Bt t$t k$jI$t s Bsj -Z {s}sA$j$k BP d p PB s JZsI }$}j$t RkR8

2x performance

AGP/PCI

GA

RE

GA

RE

Monitor

I/O

Dual pipeline, single display )LJXUH _ssjjj s{Y${Z PB8 n*NV 7 >d1H

3DUDOOHOLVP LQ *UDSKLFV &DUGV

4x performance AGP/PCI

I/O

GA

RE

GA

RE

GA

RE

GA

RE

Monitor

Quad pipeline, single display )LJXUH _ssjjj s{Y${Z PB8 n*NV 7 >d1H

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+HZOHWW3DFNDUG 3URGXFWV

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2YHUYLHZ RI 3DUDOOHO *UDSKLFV +DUGZDUH

1, 2, 4 or 8 Gamma G3 / Glint R4 rasterizer pairs

AGP 4X

Vertex stream

Transform complete vertex stream, divert fragments that touch pair's strip to rasterizer, pass on fragments that touch other strips

Gamma G3

Gamma G3

Gamma G3

Gamma G3

Glint R4

Glint R4

Glint R4

Glint R4

64 MB

64 MB

64 MB

64 MB

Each rasterizers handles its own stripes

Use RAMDAC of one chip

Video Display Bus

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{Y$} qYR RZjR s Yt Rt Bt B Y -Z {Y$}R B I${jk B Y sR {Y$}R $t {sR Y -Z 8s}}$t RZARkR8 $R tB $tRsjjI qY ZtAZ&I }sY }sRRR Iss I${jk YBZY Y $tPs{ {Y$} B Y -Z stI sR {Y$}R qY bBTI$8tR$Btsj }sY ZtR I${jk YBZY Y $tPs{ {Y$} B Y -Z stI sR {Y$}R qY bBTI$8tR$Btsj Rasterizer 1

Rasterizer 1 Rasterizer 2

Rasterizer 2

Rasterizer 1

Both Only a fraction of the polygons are processed by both rasterizers.

Rasterizer 2

)LJXUH *$R$AZ$t R$}R B sR$9R w]BZRk BP W q% >1HD

3DUDOOHOLVP LQ *UDSKLFV &DUGV

up to 8

Geometry Chip Texture Accelerator

Host PCI2.1 66 MHz 64 bits

Geometry Chip

SDRAM

Geometry Chip

Texture 200 MHz 41 bits Chip

Interface Chip

Texture cache RAM

SDRAM

Texture Chip

Raster Chip

Raster Chip

Raster Chip

Raster Chip

SDRAM

SDRAM

SDRAM

SDRAM

Rasterizer

Video Chip

Video refresh data

RGB Video Data

200 MHz 44 bits

200 MHz 33 bits

...

Geometry accelerator

Frame buffer RAM

Video control bus

)LJXUH ]Y$}Tj%j I$ss8 BP Y zy7=VNye P- }BIZ{ w]BZRk BP * 7{B sj >1E1HD

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2YHUYLHZ RI 3DUDOOHO *UDSKLFV +DUGZDUH

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6*, 3URGXFWV 6LOLFRQ *UDSKLFV ,QF qY ytht$isj$k RkR8 >dMH $R s RBT8$IIj s{Y${Z stI $R IT }${I $t 3$Z ; qY RkR8 {Bts$tR Y I$R$t{ ABsI k}RU Y pB8k isR 8Bk stI *$R}jsk ptsB ABsIR qY pB8k ABsI {B8}$RR s YBR {B8}Z $tPs{ sR bjj sR {B88stI $t}sT $Bt stI B8k I$R$AZ$Bt jB${ stI PBZ pB8k et$t }B{RRBR $t s y* sst8t es{Y isR 8Bk ABsI {B8}$RR s R$tj

3DUDOOHOLVP LQ *UDSKLFV &DUGV

Ps8t tsB b$Y s R$tj {B}k BP -Z 88Bk M( $8s tT $tR stI tBZY Ps8AZ& 88Bk B sjjB{s xd1 A$R } }$-j B s d1M(-d(1; Ps8AZ& qY I$R}jsk tsB ABsI {Bts$tR YsIbs B I$% Z} B $Y I$R}jsk BZ}Z {YsttjR s{Y b$Y $R Bbt %$IB $8$t tsB %$IB R$9 YsIbs s88s {B{$Bt stI I$$sjTBTstsjB {Bt%R$Bt YsIbs 7kR8R {st A {BthZI b$Y Bt bB B PBZ sR 88Bk ABsIR RZj$t $t Bt bB B PBZ Ps8t tsBR stI M( dE( B n1( $8s t$tR 3$Z ; RYBbR s AjB{, I$ss8 BP Y 8s-$8Z8 {BthZs$Bt b$Y PBZ pB8k et$tR PBZ isR 8Bk ABsIR stI s *$R}jsk ptsB ABsI b$Y $Y BZ}Z {YsttjR *$R}jsk j$RR *$R}jsk j$R }B{RR$t $R YstIjI $t bB bskR 3$R {B8T }$jI I$R}jsk j$R BA`{R s RBI $t Y YBR 88Bk $t RZ{Y s bsk Ys jsP I$R}jsk BA`{R {st A X}ZjjI" $tB Y s}Y${R RZARkR8 ZR$t *V stRPR R Z} Ak Y

2YHUYLHZ RI 3DUDOOHO *UDSKLFV +DUGZDUH

Host System Bus Geometry Board Host Interface Processor Geometry Distributor Geometry Engine

Geometry Engine

Geometry Engine

Geometry Engine

Geometry-Raster FIFO Vertex Bus Fragment Generator

Fragment Generator

Fragment Generator

Fragment Generator

Raster Memory Board

Raster Memory Board

Raster Memory Board

Raster Memory Board

Image Engines

Display Gen. Board De-Interleaver Display Channel

Display Channel

Display Channel

...

Display Channel

)LJXUH 7py s}Y${R s{Y${Z w]BZRk BP F 7 Btk8 sj >dMHD

V }B$Bt BP Y bB,$t 88Bk $R ZRI sR s JZZ PB $t{B8$t %Iss V{{BI$tjk s{Y BP Y Y {BR {st }PB8 bB sIR stI Bt b$ } $tRZ{$Bt B bB,$t 88Bk WB Ys bB,$t 88Bk sjjBbR Iss B A RYsI sR$jk s8Bt {BR pB8kTisR 3y3! qY BZ}Z Rs8R PB8 Y PBZ pB8k etT $tR s 8I $tB s R$tj Rs8 Ak Y pB8kTisR 3y3! qY$R

3DUDOOHOLVP LQ *UDSKLFV &DUGV

3y3! 8sk YBjI ExxnE %${R qY 8I B8k t$t BZ}Z $R b$t YBZY Y 3y3! B Y z- ZR qY pB8kTisR 3y3! {Bts$tR s 1xETbBI RYsIBb iV bY${Y ,}R s {B}k BP Y jsR %sjZR BP Y 3s8t ptsB stI y8s et$t {BtBj $RR k j$8$T ts$t Y tI PB Y pB8k et$tR B s$t RYsIBbI sR Rs $t Y$ jB{sj iVR Y RYsIBb iV }8$R sR 8BI {YstR B A }B{RRI Ak Btjk Bt BP Y pB8k et$tR z- AZR qY ytht$isj$k RkR8 8}jBkR s z- ZR B stRP Btjk R{t R}s{ %- $tPB8s$Bt z- ZR Iss $R ABsI{sR B sjj 3s8t ptsBR qY z- ZR }BB{Bj RZ}}BR Y !}tpN $T stj R$} stI $stj Pst {BtRZ{R RB Y z- ZR jBsI {BR}BtIR {jBRjk B Y jBsI Bt Y YBRTBTs}Y${R AZR qY pB8k et$t $T stj R$} bB,jBsI $R IZ{I Ak sBZtI E( }{t Ak tB {sj{Zjs$t $stj RZ} $tPB8s$Bt

2YHUYLHZ RI 3DUDOOHO *UDSKLFV +DUGZDUH

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computation complete

intesection found

ProcessA ProcessA )LJXUH isk s{$t bY Bt }B{RR {Bts$tR Y t$ R{t

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ray tracing start

ProcessA

trace first cell no intersection: move on to next cell

ProcessA

scene is not stored in this process: transfer partial scene

computation complete

receive partial scene

intersection found

ProcessA

ProcessA

send partial scene

ProcessB

ProcessB

ProcessB

ProcessB

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ray tracing start

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trace first cell scene is not stored no intersection: in this process: move on to next cell transfer ray data send ray data

ProcessA

ProcessA

ProcessA

ProcessA ProcessA scene is not stored in this process: transfer ray data again send ray data receive ray data

ProcessB

ProcessB

ProcessB

ProcessB receive ray data continue tracing in this process's scene

ProcessC

ProcessC

ProcessC

ProcessC

ProcessB

intersection found

ProcessC

computation complete )LJXUH isk s{$t B% 8Zj$}j }B{RRR

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50% of the scene distributed to machine A 50% of the scene distributed to machine B

Geometry data within one scene

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Ray tracing start

Processor B

Processor A

copy ray data

transfer ray data

Ray tracing start copy ray data ray tracing

traced result

compute ray tracing

ray tracing

traced result

compute ray tracing

ray tracing

comparison of traced results

queue of traced results

comparison of traced results

transfer traced results

queue of traced results

Parallel execution of ray distribution, ray tracing, and comparison of results

traced result

compute ray tracing

queue of ray data

ray tracing

traced result

compute ray tracing

queue of ray data

ray tracing complete

ray tracing complete

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Single Entry Single Retrieve

Multiple Entry Single Retrieve

Single Entry Multiple Retrieve

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PreEntryQueue empty

Unlocked MainQueue contains data A and B.

B A MainQueue PreEntryQueue empty C

B A MainQueue PreEntryQueue A C

C B MainQueue PreEntryQueue C D

Retrieval thread acquires lock. Entry thread tries to enqueue C at the same time.

A is retrieved. Entry thread fails to acquire lock, A so enqueue C in PreEntryQueue.

Retrieval thread unlocks main queue. Entry thread tries to enqueue D.

B MainQueue PreEntryQueue C D

Entry thread successfully acquires lock. C in PreEntryQueue is processed.

D C B MainQueue PreEntryQueue empty

Enqueuing complete. MainQueue is unlocked.

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empty

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empty

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empty

Sleep in condition wait and unlock.

empty

Entry thread acquires lock.

Set new data, unlock queue, wake up retrieval thread.

empty

Retrieval thread acquires lock and takes out data.

empty

Retrieval thread unlocks queue.

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Author Biographies

Alan Chalmers is a Reader in the Department of Computer Science at the University of Bristol, UK. He has published over 80 papers in journals and international conferences on parallel photo-realistic graphics. He was the co-chairman of the recent IEEE Parallel Visualization and Graphics Symposium and is chairman of the Eurographics workshop series on Parallel Graphics and Visualisation. Recently he and Professor F. W. Jansen were the guest editors of the journal Parallel Computing for its special edition on Parallel Graphics and Visualisation. He is also currently Vice President of ACM SIGGRAPH. His research interests include the application of parallel photorealistic graphics to archaeological site visualization in order to provide a flexible tool for investigating site reconstruction and utilization. Timothy A. Davis is an assistant professor in the Computer Science Department at Clemson University where he works within the newly established DPA (Digital Production Arts) group, which trains students to produce special effects for entertainment and commercial projects. His research involves exploiting spatio-temporal coherence in a parallel environment to reduce rendering times for ray-traced animations. He received his Ph.D. from North Carolina State University and has worked in technical positions for the Environmental Protection Agency and NASA Goddard Space Flight Center. Erik Reinhard is a post-doctoral researcher at the University of Utah in the fields of parallel ray tracing and visual perception. He received a 'TWAIO' diploma in parallel computer graphics from Delft University of Technology in 1996 and a Ph.D. degree from the University of Bristol in 2000. His current research interests include algorithms and data structures for real-time ray tracing. This includes mechanisms to trade-off visual quality for interactivity and to add animation capabilities to real-time ray tracing. 369

370

Author Biographies

Kadi Bouatouch is an electronics and automatic systems engineer (ENSEM 1974). He was awarded a Ph.D. in 1977 and a higher doctorate on computer science in the fi eld of computer graphics in 1989. He is working on global illumination, lighting simulation for complex environments, parallel radiosity, computer architecture for image synthesis, virtual augmented reality, computer vision and visual comfort. He designed a VLSI chip for image synthesis. He is currently Professor at the University of Rennes 1 (France) and researcher at IRISA. He has published more than seventy papers. Toshi Kato has devoted his time to the development of high-end production-level renderers for sixteen years. Currently he is the project leader of an ongoing project “Kilauea,” a parallel ray tracer developed at Square USA’s R&D department. From 1993 to 1998 he developed an in-house scanline-based renderer at Rhythm & Hues in LA and participated in the production of movies such as Mouse Hunt (1998), Kazaam (1996) and Babe (1995). He also developed a special stereoscopic renderer for IMAX’s Omnimax Solido dome. Steven Parker is a Research Assistant Professor in the Department of Computer Science at the University of Utah. His research focuses on problem solving environments, which tie together scientifi c computing, scientifi c visualization, and computer graphics. He was a recipient of the Computational Science Graduate Fellowship from the Dept. of Energy. He received a Ph.D. from the University of Utah (1999), and B.S. in Electrical Engineering from the University of Oklahoma (1992). Tim Purcell is a third year Ph.D. student in the department of Computer Science at Stanford University. His research focuses on architectural design for hardware ray tracing. He was a recipient of the Graduate Research Fellowship from the National Science Foundation. He received a B.S. in Computer Science from the University of Utah in 1998.

Philipp Slusallek is a professor at the computer graphics lab at Saarland University. He was visiting assistant professor at the Stanford University graphics lab (1998–1999). He received a Diploma in physics from the University of Tuebingen (1990) and a Ph.D. in computer science from the University of Erlangen (1995). He leads the Vision project, a large object-oriented, physically-based rendering system. His current research activities focus on interactive ray-tracing on off -the-shelf computers and designing a hardware architecture for real-time ray tracing.