Pharr M. (ed.) GPU Gems 2: Programming Techniques for High-Perfomance Graphics and General-Purpose Computation

Addison-Wesley, 2005. — 834 p. — ISBN: 0-321-33559-7.The first volume of GPU Gems was conceived in the spring of 2003, soon after the arrival of the first generation of fully programmable GPUs. The resulting book was released less than a year later and quickly became a best seller, providing a snapshot of the best ideas for making the most of the capabilities of the latest programmable graphics hardware.
GPU programming is a rapidly changing field, and the time is already ripe for a sequel. In the handful of years since programmable graphics processors first became available, they have become faster and more flexible at an incredible pace. Early programmable GPUs supported programmability only at the vertex level, while today complex per-pixel programs are common. A year ago, real-time GPU programs were typically tens of instructions long, while this year's GPUs handle complex programs hundreds of instructions long and still render at interactive rates. Programmable graphics has even transcended the PC and is rapidly spreading to consoles, handheld gaming devices, and mobile phones.
Until recently, performance-conscious developers might have considered writing their GPU programs in assembly language. These days, however, high-level GPU programming languages are ubiquitous. It is extremely rare for developers to bother writing assembly for GPUs anymore, thanks both to improvements in compilers and to the rapidly increasing capabilities of GPUs. (In contrast, it took many more years before game developers switched from writing their games in CPU assembly language to using higher-level languages.)
This sort of rapid change makes a "gems"-style book a natural fit for assembling the state of the art and disseminating it to the developer community. Featuring chapters written by acknowledged experts, GPU Gems 2 provides broad coverage of the most exciting new ideas in the field.
Innovations in graphics hardware and programming environments have inspired further innovations in how to use programmability. While programmable shading has long been a staple of offline software rendering, the advent of programmability on GPUs has led to the invention of a wide variety of new techniques for programmable shading. Going far beyond procedural pattern generation and texture composition, the state of the art of using shaders on GPUs is rapidly breaking completely new ground, leading to novel techniques for animation, lighting, particle systems, and much more.
Indeed, the flexibility and speed of GPUs have fostered considerable interest in doing computations on GPUs that go beyond computer graphics: general-purpose computation on GPUs, or "GPGPU." This volume of the GPU Gems series devotes a significant number of chapters to this new topic, including an overview of GPGPU programming techniques as well as in-depth discussions of a number of representative applications and key algorithms. As GPUs continue to increase in performance more quickly than CPUs, these topics will gain in importance for more and more programmers because GPUs will provide superior results for many computationally intensive applications.
With this background, we sent out a public call for participation in GPU Gems 2 . The response was overwhelming: more than 150 chapters were proposed in the short time that submissions were open, covering a variety of topics related to GPU programming. We were able to include only about a third of them in this volume; many excellent submissions could not be included purely because of constraints on the physical size of the book. It was difficult for the editors to whittle down the chapters to the 48 included here, and we would like to thank everyone who submitted proposals.
The accepted chapters went through a rigorous review process in which the book's editors, the authors of other chapters in the same part of the book, and in some cases additional reviewers from NVIDIA carefully read them and suggested improvements or changes. In almost every case, this step noticeably improved the final chapter, due to the high-quality feedback provided by the reviewers. We thank all of the reviewers for the time and effort they put into this important part of the production process.Part I Geometric Complexity
Toward Photorealism in Virtual Botany
Terrain Rendering Using GPU-Based Geometry Clipmaps
Inside Geometry Instancing
Segment Buffering
Optimizing Resource Management with Multistreaming
Hardware Occlusion Queries Made Useful
Adaptive Tessellation of Subdivision Surfaces with Displacement Mapping
Per-Pixel Displacement Mapping with Distance Functions
Part II Shading, Lighting, and Shadows
Deferred Shading in S.T.A.L.K.E.R.
Real-Time Computation of Dynamic Irradiance Environment Maps
Approximate Bidirectional Texture Functions
Tile-Based Texture Mapping
Implementing the mental images Phenomena Renderer on the GPU
Dynamic Ambient Occlusion and Indirect Lighting
Blueprint Rendering and "Sketchy Drawings"
Accurate Atmospheric Scattering
Efficient Soft-Edged Shadows Using Pixel Shader Branching
Using Vertex Texture Displacement for Realistic Water Rendering
Generic Refraction Simulation
Part III High-Quality Rendering
Fast Third-Order Texture Filtering
High-Quality Antialiased Rasterization
Fast Prefiltered Lines
Hair Animation and Rendering in the Nalu Demo
Using Lookup Tables to Accelerate Color Transformations
GPU Image Processing in Apple's Motion
Implementing Improved Perlin Noise
Advanced High-Quality Filtering
Mipmap-Level Measurement
Part IV General-Purpose Computation on GPUS: A Primer
Streaming Architectures and Technology Trends
The GeForce 6 Series GPU Architecture
Mapping Computational Concepts to GPUs
Taking the Plunge into GPU Computing
Implementing Efficient Parallel Data Structures on GPUs
GPU Flow-Control Idioms
GPU Program Optimization
Stream Reduction Operations for GPGPU Applications
Part V Image-Oriented Computing
Octree Textures on the GPU
High-Quality Global Illumination Rendering Using Rasterization
Global Illumination Using Progressive Refinement Radiosity
Computer Vision on the GPU
Deferred Filtering: Rendering from Difficult Data Formats
Conservative Rasterization
Part VI Simulation and Numerical Algorithms
GPU Computing for Protein Structure Prediction
A GPU Framework for Solving Systems of Linear Equations
Options Pricing on the GPU
Improved GPU Sorting
Flow Simulation with Complex Boundaries
Medical Image Reconstruction with the FFT