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E-raamat: Practical Parallel Rendering [Taylor & Francis e-raamat]

Edited by (University of Warwick, Coventry, UK), Edited by , Edited by
  • Formaat: 392 pages
  • Ilmumisaeg: 30-Jun-2020
  • Kirjastus: CRC Press
  • ISBN-13: 9780429294952
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  • Taylor & Francis e-raamat
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Practical Parallel RenderingSuurem pilt
  • Formaat: 392 pages
  • Ilmumisaeg: 30-Jun-2020
  • Kirjastus: CRC Press
  • ISBN-13: 9780429294952
Teised raamatud teemal:
Taylor & Francis e-raamatudRohkem infot Taylor & Francis e-raamatute kohta
Raamatu kodulehekülg: https://www.taylorfrancis.com/books/9780429294952
Meeting the growing demands for speed and quality in rendering computer graphics images requires new techniques. Practical parallel rendering provides one of the most practical solutions. This book addresses the basic issues of rendering within a parallel or distributed computing environment, and considers the strengths and weaknesses of multiprocessor machines and networked render farms for graphics rendering. Case studies of working applications demonstrate, in detail, practical ways of dealing with complex issues involved in parallel processing.
Preface xi
I Parallel Rendering
1(184)
1 Introduction to Parallel Processing
3(28)
1.1 Concepts
4(3)
1.1.1 Dependencies
5(1)
1.1.2 Scalability
6(1)
1.1.3 Control
7(1)
1.2 Classification of Parallel Systems
7(7)
1.2.1 Parallel versus Distributed Systems
13(1)
1.3 The Relationship of Tasks and Data
14(3)
1.3.1 Inherent Difficulties
15(1)
1.3.2 Tasks
16(1)
1.3.3 Data
16(1)
1.4 Evaluating Parallel Implementations
17(14)
1.4.1 Realization Penalties
18(2)
1.4.2 Performance Metrics
20(5)
1.4.3 Efficiency
25(6)
2 Task Scheduling and Data Management
31(58)
2.1 Problem Decomposition
31(5)
2.1.1 Algorithmic Decomposition
32(1)
2.1.2 Domain Decomposition
32(2)
2.1.3 Abstract Definition of a Task
34(1)
2.1.4 System Architecture
34(2)
2.2 Computational Models
36(10)
2.2.1 Data Driven Model
36(5)
2.2.2 Demand Driven Model
41(5)
2.2.3 Hybrid Computational Model
46(1)
2.3 Task Management
46(7)
2.3.1 Task Definition and Granularity
46(2)
2.3.2 Task Distribution and Control
48(1)
2.3.3 Algorithmic Dependencies
49(4)
2.4 Task Scheduling Strategies
53(12)
2.4.1 Data Driven Task Management Strategies
53(1)
2.4.2 Demand Driven Task Management Strategies
54(5)
2.4.3 Task Manager Process
59(3)
2.4.4 Distributed Task Management
62(2)
2.4.5 Preferred Bias Task Allocation
64(1)
2.5 Data Management
65(24)
2.5.1 World Model of the Data: No Data Management Required
66(1)
2.5.2 Virtual Shared Memory
67(2)
2.5.3 The Data Manager
69(7)
2.5.4 Consistency
76(4)
2.5.5 Minimizing the Impact of Remote Data Requests
80(5)
2.5.6 Data Management for Multistage Problems
85(4)
3 Parallel Global Illumination Algorithms
89(44)
3.1 Rendering
90(2)
3.2 Parallel Processing
92(2)
3.3 Ray Tracing
94(2)
3.4 Spatial Subdivisions
96(13)
3.4.1 Parallel Ray Tracing
99(1)
3.4.2 Demand Driven Ray Tracing
99(5)
3.4.3 Data Parallel Ray Tracing
104(3)
3.4.4 Hybrid Scheduling
107(2)
3.5 Radiosity
109(3)
3.5.1 Form Factors
110(1)
3.5.2 Parallel Radiosity
111(1)
3.6 Full Matrix Radiosity
112(4)
3.6.1 Setting Up the Matrix of Form Factors
113(2)
3.6.2 Solving the Matrix of Form Factors
115(1)
3.6.3 Group Iterative Methods
115(1)
3.7 Progressive Refinement
116(4)
3.7.1 Parallel Shooting
118(2)
3.8 Hierarchical Radiosity
120(2)
3.8.1 Parallel Hierarchical Radiosity
121(1)
3.9 Particle Tracing
122(3)
3.9.1 Parallel Particle Tracing
123(1)
3.9.2 Density Estimation
124(1)
3.10 Data Distribution and Data Locality
125(6)
3.10.1 Data Distribution
126(1)
3.10.2 Visibility Preprocessing
127(1)
3.10.3 Environment Mapping
128(1)
3.10.4 Geometric Simplification
128(2)
3.10.5 Directional Caching
130(1)
3.10.6 Reordering Computations
130(1)
3.11 Discussion
131(2)
4 Overview of Parallel Graphics Hardware
133(20)
4.1 Pipelining
133(3)
4.2 Parallelism in Graphics Cards
136(15)
4.2.1 3DLABS Products
136(3)
4.2.2 Hewlett-Packard Products
139(3)
4.2.3 SGI Products (Silicon Graphics, Inc.)
142(4)
4.2.4 UNC Products
146(3)
4.2.5 Pomegranate Graphics Chip
149(2)
4.3 Conclusion
151(2)
5 Coherence in Ray Tracing
153(32)
5.1 Scene Analysis
154(11)
5.1.1 Distribution of Data Accesses
155(3)
5.1.2 Temporal Characteristics
158(4)
5.1.3 Temporal Behaviour per Ray Type
162(2)
5.1.4 Conclusions
164(1)
5.2 Animation Analysis
165(20)
5.2.1 Background
166(1)
5.2.2 Related Work
167(2)
5.2.3 Frame Coherence Algorithm
169(5)
5.2.4 Parallel Frame Coherence Algorithm
174(2)
5.2.5 Results
176(8)
5.2.6 Summary
184(1)
II Case Studies
185(152)
6 Interactive Ray Tracing on a Supercomputer
187(30)
6.1 System Architecture
188(6)
6.1.1 Conventional Operation
189(3)
6.1.2 Frameless Rendering
192(1)
6.1.3 Performance
193(1)
6.2 Ray Tracing for Volume Visualization
194(20)
6.2.1 Background
195(2)
6.2.2 Traversal Optimizations
197(4)
6.2.3 Algorithms
201(4)
6.2.4 Results
205(6)
6.2.5 Discussion
211(3)
6.3 Ray Tracing for Terrain Visualization
214(1)
6.4 Conclusions
215(2)
7 Interactive Ray Tracing on PCs
217(32)
7.1 Introduction
217(4)
7.1.1 Previous Work
220(1)
7.2 An Optimized Ray Tracing Implementation
221(2)
7.2.1 Code Complexity
221(1)
7.2.2 Caching
222(1)
7.2.3 Coherence through Packets of Rays
223(1)
7.2.4 Parallelism through SIMD Extensions
223(1)
7.3 Ray Triangle Intersection Computation
223(3)
7.3.1 Optimized Barycentric Coordinate Test
223(1)
7.3.2 Evaluating Instruction Level Parallelism
224(1)
7.3.3 SIMD Barycentric Coordinate Test
224(2)
7.4 BSP Traversal
226(3)
7.4.1 Traversal Algorithm
226(2)
7.4.2 Memory Layout for Better Caching
228(1)
7.4.3 Traversal Overhead
229(1)
7.5 SIMD Phong Shading
229(2)
7.6 Performance of the Ray Tracing Engine
231(5)
7.6.1 Comparison to Other Ray Tracers
231(2)
7.6.2 Reflection and Shadow Rays
233(1)
7.6.3 Comparison with Rasterization Hardware
234(2)
7.7 Interactive Ray Tracing on PC Clusters
236(3)
7.7.1 Overview
238(1)
7.8 Distributed Data Management
239(2)
7.8.1 Explicit Data Management
239(2)
7.8.2 Preprocessing
241(1)
7.9 Load Balancing
241(1)
7.10 Implementation
242(1)
7.11 Results
243(3)
7.12 Conclusions
246(3)
8 The "Kilauea" Massively Parallel Ray Tracer
249(80)
8.1 What Is the Kilauea Project?
249(1)
8.2 Basic Idea
250(1)
8.3 System Design
251(5)
8.3.1 Hardware Environment
251(1)
8.3.2 Pthreads
252(1)
8.3.3 Message Passing
252(1)
8.3.4 Front-End Process
253(1)
8.3.5 Launching Kilauea
253(1)
8.3.6 Single Executable Binary
254(1)
8.3.7 Multiframe Rendering
254(1)
8.3.8 Global Illumination Renderer
255(1)
8.4 The ShotData File Format
256(5)
8.5 Parallel Ray Tracing
261(7)
8.6 Implementation
268(48)
8.6.1 Low-Level Data Structure
268(9)
8.6.2 MPI (Message Passing Interface) Layer
277(2)
8.6.3 Tel Command Interface
279(2)
8.6.4 Rank and Task
281(7)
8.6.5 Details of Ray Tracing
288(3)
8.6.6 Shading Computation
291(15)
8.6.7 Photon Map Method
306(4)
8.6.8 Things to Note in Shading Computation
310(4)
8.6.9 Development in General
314(2)
8.7 Rendering Results
316(7)
8.7.1 Sample 1: Quatro
316(3)
8.7.2 Sample 2: Jeep
319(2)
8.7.3 Sample 3: Jeep 8
321(1)
8.7.4 Consideration of Rendering Results
322(1)
8.8 Conclusion
323(2)
8.9 Future Plans and Tasks
325(4)
9 Parallel Ray Tracing on a Chip
329(8)
9.1 The Smart Memories Chip
329(2)
9.2 The SHARP Ray Tracer
331(2)
9.3 Simulation Results
333(3)
9.3.1 Caching
334(1)
9.3.2 Estimated Performance
335(1)
9.4 Conclusions
336(1)
Bibliography 337(26)
Index 363(6)
Author Biographies 369
Alan Charmers
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