The CD content, including demos and content, is available on the web and for download.
Part I: Geometric Complexity
Today's games are visually more interesting and complex than ever before. Geometric complexity—how many objects are visible and how detailed each looks—is one of the dimensions in which games are making leaps and bounds.
Advances in technology are partly responsible for these leaps and bounds: CPUs, memory, and buses all have become faster, but specifically GPUs are undergoing significant change and are becoming ever more powerful—at a rate faster than Moore's Law.
These GPU changes include incorporating fixed-function processing for the vertex- and pixel-shading units, then generalizing those to be fully programmable. GPUs also have gained more units to process pixels and vertices in parallel: the GeForce 6800 Ultra, for example, incorporates 6 vertex shader units and 16 pixel pipelines.
Despite these performance advances, rendering complex scenes is still more difficult than simply dumping all geometry onto the GPU and forgetting about it. The simple approach tends to fail either because the generated GPU workload turns out to be excessive, or because the associated CPU overhead is prohibitive. This part of the book discusses the challenges today's games face in rendering complex geometric scenes.
Chapter 1, "Toward Photorealism in Virtual Botany" by David Whatley of Simutronics Corporation, provides a holistic view on how to render nature scenes. It explains the multitude of different techniques, from scene management and rendering various plant layers to post-processing effects, that Simutronics' Hero's Journey employs to generate complex and stunning visuals.
Rendering terrain is a good example of why simply dumping all available data to the GPU cannot work: the horizon represents a near-infinite amount of vertex data and thus workload. Arul Asirvatham and Hugues Hoppe of Microsoft Research use vertex texture fetches for a new highly efficient terrain-rendering algorithm. Their technique avoids overloading the GPU even as it shifts most work onto the GPU and away from the CPU, which too often is the bottleneck in modern games. Chapter 2, "Terrain Rendering Using GPU-Based Geometry Clipmaps," provides all the implementation details.
As already mentioned, another way to increase geometric complexity is to increase the number of visible objects in a scene. The straightforward solution of drawing each object independently of the others, however, quickly bogs down even a high-end system. It is much easier to efficiently draw ten objects that are one million triangles each, than it is to draw one million objects that are ten triangles each. Francesco Carucci of Lionhead Studios faces this very problem while developing Black & White 2, the sequel to Lionhead's critically acclaimed Black & White. Chapter 3, "Inside Geometry Instancing," describes his solution: a framework of instancing techniques that applies to legacy GPUs as well as to GPUs supporting DirectX 9's instancing API. Jon Olick of 2015 provides further optimizations to the instancing technique that prove beneficial for 2015's title Men of Valor: Vietnam. Jon describes his findings in Chapter 4, "Segment Buffering."
Also, as games incorporate more and more data—more complex scenes of more complex meshes rendered in multiple, disparate passes supporting the gamut of differing functionality from legacy to current high-end GPUs—managing this glut of data efficiently becomes paramount. Oliver Hoeller and Kurt Pelzer of Piranha Bytes are currently working on Piranha Bytes' Gothic III engine. They share their solutions in Chapter 5, "Optimizing Resource Management with Multistreaming."
The best way to render lots of geometry to create geometric complexity is to avoid rendering the occluded parts. Michael Wimmer and Jirí Bittner of the Vienna University of Technology explore how best to apply that idea in Chapter 6, "Hardware Occlusion Queries Made Useful." Occlusion queries are a GPU feature that provides high-latency feedback on whether an object is visible or not after it is rendered. Unlike earlier occlusion-query culling techniques, Michael and Jirí's algorithm is pixel-perfect. That is, it introduces no rendering artifacts, generates a near-optimal set of visible objects to render, does not put unnecessary load on the GPU, and has minimal CPU overhead.
Similarly, increasing geometric detail only where visible and simplifying it when and where it isn't visible is a good way to avoid excessive GPU loads. View-dependent and adaptive subdivision schemes are an appealing solution that the offline-rendering world already employs to render their highly detailed models to subpixel geometric accuracy. Subdivision surfaces have not yet found a place in today's real-time applications, partly because they are not directly supported in graphics hardware. Rendering subdivision surfaces thus seems out of reach for real-time applications. Not so, says Michael Bunnell of NVIDIA Corporation. In Chapter 7, Michael shows how his implementation of "Adaptive Tessellation of Subdivision Surfaces with Displacement Mapping" is already feasible on modern GPUs and results in movie-quality geometric detail at real-time rates.
Finally, faking geometric complexity with methods that are cheaper than actually rendering geometry allow for higher apparent complexity at faster speeds. Replacing geometry with textures that merely depict it used to be an acceptable trade-off—and in the case of grates and wire-mesh fences, often still is. Normal mapping is a more sophisticated fake that properly accounts for lighting information. Parallax mapping is the latest craze that attempts to also account for intra-object occlusions. William Donnelly of the University of Waterloo one-ups parallax mapping: he describes "Per-Pixel Displacement Mapping with Distance Functions" in Chapter 8. Displacement mapping provides correct intra-object occlusion information, yet minimally increases computation cost. His technique gives excellent results while taking full advantage of the latest programmable pixel-shading hardware. Even better, it is practical for applications today.
Matthias Wloka, NVIDIA Corporation
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Library of Congress Cataloging-in-Publication Data
GPU gems 2 : programming techniques for high-performance graphics and general-purpose
computation / edited by Matt Pharr ; Randima Fernando, series editor.
Includes bibliographical references and index.
ISBN 0-321-33559-7 (hardcover : alk. paper)
1. Computer graphics. 2. Real-time programming. I. Pharr, Matt. II. Fernando, Randima.
GeForce™ and NVIDIA Quadro® are trademarks or registered trademarks of NVIDIA Corporation.
Nalu, Timbury, and Clear Sailing images © 2004 NVIDIA Corporation.
mental images and mental ray are trademarks or registered trademarks of mental images, GmbH.
Copyright © 2005 by NVIDIA Corporation.
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form, or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior consent of the publisher. Printed in the United States of America. Published simultaneously in Canada.
For information on obtaining permission for use of material from this work, please submit a written request to:
Pearson Education, Inc.
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Text printed in the United States on recycled paper at Quebecor World Taunton in Taunton, Massachusetts.
Second printing, April 2005
To everyone striving to make today's best computer graphics look primitive tomorrow
- Inside Back Cover
- Inside Front Cover
- Part I: Geometric Complexity
- Chapter 1. Toward Photorealism in Virtual Botany
- Chapter 2. Terrain Rendering Using GPU-Based Geometry Clipmaps
- Chapter 3. Inside Geometry Instancing
- Chapter 4. Segment Buffering
- Chapter 5. Optimizing Resource Management with Multistreaming
- Chapter 6. Hardware Occlusion Queries Made Useful
- Chapter 7. Adaptive Tessellation of Subdivision Surfaces with Displacement Mapping
- Chapter 8. Per-Pixel Displacement Mapping with Distance Functions
- Part II: Shading, Lighting, and Shadows
- Chapter 10. Real-Time Computation of Dynamic Irradiance Environment Maps
- Chapter 11. Approximate Bidirectional Texture Functions
- Chapter 12. Tile-Based Texture Mapping
- Chapter 13. Implementing the mental images Phenomena Renderer on the GPU
- Chapter 14. Dynamic Ambient Occlusion and Indirect Lighting
- Chapter 15. Blueprint Rendering and "Sketchy Drawings"
- Chapter 16. Accurate Atmospheric Scattering
- Chapter 17. Efficient Soft-Edged Shadows Using Pixel Shader Branching
- Chapter 18. Using Vertex Texture Displacement for Realistic Water Rendering
- Chapter 19. Generic Refraction Simulation
- Chapter 9. Deferred Shading in S.T.A.L.K.E.R.
- Part III: High-Quality Rendering
- Chapter 20. Fast Third-Order Texture Filtering
- Chapter 21. High-Quality Antialiased Rasterization
- Chapter 22. Fast Prefiltered Lines
- Chapter 23. Hair Animation and Rendering in the Nalu Demo
- Chapter 24. Using Lookup Tables to Accelerate Color Transformations
- Chapter 25. GPU Image Processing in Apple's Motion
- Chapter 26. Implementing Improved Perlin Noise
- Chapter 27. Advanced High-Quality Filtering
- Chapter 28. Mipmap-Level Measurement
- Part IV: General-Purpose Computation on GPUS: A Primer
- Chapter 29. Streaming Architectures and Technology Trends
- Chapter 30. The GeForce 6 Series GPU Architecture
- Chapter 31. Mapping Computational Concepts to GPUs
- Chapter 32. Taking the Plunge into GPU Computing
- Chapter 33. Implementing Efficient Parallel Data Structures on GPUs
- Chapter 34. GPU Flow-Control Idioms
- Chapter 35. GPU Program Optimization
- Chapter 36. Stream Reduction Operations for GPGPU Applications
- Part V: Image-Oriented Computing
- Chapter 37. Octree Textures on the GPU
- Chapter 38. High-Quality Global Illumination Rendering Using Rasterization
- Chapter 39. Global Illumination Using Progressive Refinement Radiosity
- Chapter 40. Computer Vision on the GPU
- Chapter 41. Deferred Filtering: Rendering from Difficult Data Formats
- Chapter 42. Conservative Rasterization
- Part VI: Simulation and Numerical Algorithms
- Chapter 43. GPU Computing for Protein Structure Prediction
- Chapter 44. A GPU Framework for Solving Systems of Linear Equations
- Chapter 45. Options Pricing on the GPU
- Chapter 46. Improved GPU Sorting
- Chapter 47. Flow Simulation with Complex Boundaries
- Chapter 48. Medical Image Reconstruction with the FFT