?GPU Gems 2 isn?t meant to simply adorn your bookshelf?it?s required reading for anyone trying to keep pace with the rapid evolution of programmable graphics. If you?re serious about graphics, this book will take you to the edge of what the GPU can do.?

?Remi Arnaud, Graphics Architect at Sony Computer Entertainment?The topics covered in GPU Gems 2 are critical to the next generation of game engines.?

?Gary McTaggart, Software Engineer at Valve, Creators of Half-Life and Counter-Strike

This sequel to the best-selling, first volume of GPU Gems details the latest programming techniques for today?s graphics processing units (GPUs). As GPUs find their way into mobile phones, handheld gaming devices, and consoles, GPU expertise is even more critical in today?s competitive environment. Real-time graphics programmers will discover the latest algorithms for creating advanced visual effects, strategies for managing complex scenes, and advanced image processing techniques. Readers will also learn new methods for using the substantial processing power of the GPU in other computationally intensive applications, such as scientific computing and finance. Twenty of the book?s forty-eight chapters are devoted to GPGPU programming, from basic concepts to advanced techniques. Written by experts in cutting-edge GPU programming, this book offers readers practical means to harness the enormous capabilities of GPUs.

Major topics covered include:

• Geometric Complexity
• Shading, Lighting, and Shadows
• High-Quality Rendering
• General-Purpose Computation on GPUs: A Primer
• Image-Oriented Computing
• Simulation and Numerical Algorithms

Contributors are from the following corporations and universities:

1C: Maddox Games
2015
Apple Computer
Armstrong State University
Climax Entertainment
Crytek
discreet
ETH Zurich
GRAVIR/IMAG?INRIA
GSC Game World
Lionhead Studios
Lund University
Massachusetts Institute of Technology
mental images
Microsoft Research
NVIDIA Corporation
Piranha Bytes
Siemens Corporate Research
Siemens Medical Solutions
Simutronics Corporation
Sony Pictures Imageworks
Stanford University
Stony Brook University
Technische Universität München
University of California, Davis
University of North Carolina at Chapel Hill
University of Potsdam
University of Tokyo
University of Toronto
University of Utah
University of Virginia
University of Waterloo
Vienna University of Technology
VRVis Research Center

Section editors include NVIDIA engineers: Kevin Bjorke, Cem Cebenoyan, Simon Green, Mark Harris, Craig Kolb, and Matthias Wloka

The accompanying CD-ROM includes complementary examples and sample programs.

Matt Pharr is a software engineer at NVIDIA. Matt is also the coauthor of the book Physically Based Rendering: From Theory to Implementation (Morgan Kaufmann, 2004).

Randima (Randy) Fernando is Manager of Developer Education at NVIDIA.

One of the biggest developments in computer hardware in the last few yearshas been the introduction of a new generation of Graphics Processing Units(GPUs) with more power and flexibility than the CPU. Not only have GPUsrevolutionized graphics programming, now developers are starting to use themwherever substantial processing power is required, for instance in financial andmedical applications. This use of GPUs for more general purposes is referredto as General Purpose computation on GPUs(GPGPU).GPU Gems 2 continues the format of the first edition, with forty six chaptersthat detail cutting-edge programming techniques from some of the world’s topexperts. It goes beyond the first volume, however, in presenting in book formfor the first time methods for GPGPU programming. This book offers thereader comprehensive knowledge for harnessing the enormous capabilities ofmodern GPUs. GPGPU has the potential to bring huge changes to the waycomputers work and applications are written. (Rick Rashid of MicrosoftResearch talked about GPGPU in his keynote at OOPSLA 2004.)N.B. - the character on the cover is a mermaid named "Nalu", and is thecurrent focus of NVIDIA’s marketing campaigns. She will be immediatelyrecognizable to the target audience.

“GPU Gems 2 isn’t meant to simply adorn your bookshelf—it’s required reading for anyone trying to keep pace with the rapid evolution of programmable graphics. If you’re serious about graphics, this book will take you to the edge of what the GPU can do.”

—Remi Arnaud, Graphics Architect at Sony Computer Entertainment

“The topics covered in GPU Gems 2 are critical to the next generation of game engines.”

—Gary McTaggart, Software Engineer at Valve, Creators of Half-Life and Counter-Strike

This sequel to the best-selling, first volume of GPU Gems details the latest programming techniques for today’s graphics processing units (GPUs). As GPUs find their way into mobile phones, handheld gaming devices, and consoles, GPU expertise is even more critical in today’s competitive environment. Real-time graphics programmers will discover the latest algorithms for creating advanced visual effects, strategies for managing complex scenes, and advanced image processing techniques. Readers will also learn new methods for using the substantial processing power of the GPU in other computationally intensive applications, such as scientific computing and finance. Twenty of the book’s forty-eight chapters are devoted to GPGPU programming, from basic concepts to advanced techniques. Written by experts in cutting-edge GPU programming, this book offers readers practical means to harness the enormous capabilities of GPUs.

Major topics covered include:

• Geometric Complexity
• Shading, Lighting, and Shadows
• High-Quality Rendering
• General-Purpose Computation on GPUs: A Primer
• Image-Oriented Computing
• Simulation and Numerical Algorithms

Contributors are from the following corporations and universities:

1C: Maddox Games
2015
Apple Computer
Armstrong State University
Climax Entertainment
Crytek
discreet
ETH Zurich
GRAVIR/IMAG—INRIA
GSC Game World
Lionhead Studios
Lund University
Massachusetts Institute of Technology
mental images
Microsoft Research
NVIDIA Corporation
Piranha Bytes
Siemens Corporate Research
Siemens Medical Solutions
Simutronics Corporation
Sony Pictures Imageworks
Stanford University
Stony Brook University
Technische Universität München
University of California, Davis
University of North Carolina at Chapel Hill
University of Potsdam
University of Tokyo
University of Toronto
University of Utah
University of Virginia
University of Waterloo
Vienna University of Technology
VRVis Research Center

Section editors include NVIDIA engineers: Kevin Bjorke, Cem Cebenoyan, Simon Green, Mark Harris, Craig Kolb, and Matthias Wloka

The accompanying CD-ROM includes complementary examples and sample programs.

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 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. Intended Audience We expect readers to be familiar with the fundamentals of computer graphics and GPU programming, including graphics APIs such as Direct3D and OpenGL, as well as GPU languages such as HLSL, GLSL, and Cg. Readers interested in GPGPU programming may find it helpful to have some basic familiarity with parallel programming concepts. Developers of games, visualization applications, and other interactive applications, as well as researchers in computer graphics, will find GPU Gems 2 an invaluable daily resource. In particular, those developing for next-generation consoles will find a wealth of timely and applicable content. Trying the Examples GPU Gems 2 comes with a CD-ROM that includes code samples, movies, and other demonstrations of the techniques described in the book. This CD is a valuable supplement to the ideas explained in the book. In many cases, the working examples provided by the authors will provide additional enlightenment. You can find sample chapters, updated CD content, supplementary materials, and more at the book’s Web site, [a href="http://developer.nvidia.com/GPUGems2/"

Excellent

Firstly, I must say that I only bought this book for the chapters on GPGPU/CUDA.

Combined with nVidia’s online content and code samples its a magnificent source of information. This kind of information is otherwise widely disseminated and hard to collate. This book is very well put together and a decent reference for the initiate in removing intensive and massively parallel computation onto the GPU. My own simulations execute 30-60 times faster than on the CPU - well worth it.

The otherwise quite steep learning curve is flattened considerably by this book. Buy this book if your considering GPGPU systems.

Excellent book

Written simply and clearly, I found it really interesting to read. Tho sometimes I’d wish more maths here...

Outstanding reference

The first half (28 chapters) of this book address the needs of the graphics programming master, or master-to-be. This goes way past the basics of GPU programming and language, and dives directly into solutions of demanding problems. This includes techniques for adding complexity to a visual environment at modest cost, real-time modeling of grass in the wind, softened shadows, and dozens of other aids for efficient and believable rendering. Some techniques address non-photorealistic techniqes as well. Together, they add a big handful of new tools to the toolbox of even advanced GPU developers. (Beginners: I’m sorry, but this isn’t for you. Some day, just not today.)

I have to admit, though, my interest lies largely in the last 20 chapters. In this section, authors from university and industry research teams describe "GPGPU" - general processing on GPUs. This puts the incredible computing power of the GPU to use on tasks from linear algebra and differential equations to finance, computer vision, fluid flow, and medical imaging, instead of rendering viewable pictures. GPGPU promises huge performance increases over standard CPUs, but imposes huge barriers to realizing that promise. GPUs achieve their high performance by tailoring their physical architecture to a specific class of computations. That class is large, granted, but still covers only a tiny portion of today’s compute-intensive tasks - and if your computation doesn’t match the GPU model, you’re just out of luck. These chapters offer tips’n’tricks for overcoming the architectural barrier, for rethinking applications in terms that GPUs can handle effectively.

GPGPU has been around for only a few years, largely as isolated acts of individual cleverness. No organized body of knowledge and practice exists for explointing this computational resource, and none seems likely to exist for some years to come. Every body of knowledge goes through that stage, "button collecting" of scattered, unrelated facts, the necessary elements from which larger patterns will some day be drawn. This collection, even if hit-or-miss for any one reader’s needs, does its part to collect today’s techniques and to disseminate that knowledge. Maybe some day, GPGPU will be as common and systematic as C programming is today - until then, anthologies like this are what we have, and this is a good one.

-- wiredweird

GPU??????????????

??"GPU Gems"??????????????"Game Programming Gems"?????????48???????????????????????????6????????????????????????????????????????????????????????????????????

????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????

???NVIDIA??????????????NVIDIA????

A comprehensive resource - but not for the novice

Truly Matt Pharr and NVIDIA are at the top of their game, and his "GPU Gems" series is certainly the only one of its kind for graphics professionals that are familiar with GPU’s and shading languages already, and want to exploit them for the maximum speed and effect achievable using today’s technology. It is not a "how-to" book on shading or GPUs or even advanced graphics. There are equations and code interspersed throughout the book, with bits of wisdom that are very instructive for the initiated. However, if you are a home-grown graphics programmer who knows C, or C++, or Java, and even some assembly language, plus you are familiar with image processing and computer graphics techniques, that will probably not be enough to get you through this book. I would say that this is a five star book for high-level professional graphics programmers who work with GPU specifics and shaders daily, and I would say it is a two or three star book for everyone else.
If you want a good introduction into the concept of writing shaders plus practice with an actual shading language, try "OpenGL Shading Language, 2nd Edition" by Rost, assuming you already know OpenGL. For a great on-line resource for modeling and graphics that will get you going in the right direction of knowing what the authors of these articles know, type "Elias Hugo" into Google and check out the first address shown. There is a wealth of on-line articles, complete with math and pseudocode, available there. Then, maybe, you will be ready to sift some knowledge from this "GPU Gems" series.
I notice that the table of contents is not shown by Amazon, so I list the articles here:
PART 1:GEOMETRIC COMPLEXITY
Towards Photorealism in Virtual Botany
Terrain Rendering using GPU-Based Geometry Clipmaps
Inside Geometry Instancing
Segment Buffering
Optimizing Resource Management with Multi-Streaming
Hardware Occlusion Queries Made Useful
Adaptive Tessellation of Subdivision Surfaces with Displacement Mapping
Per-Pixel Displacement Mapping with Distance Functions
PART 2:SHADING, LIGHTING, AND SHADOWS
Deferred Shading in STALKER
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 3: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 4:GENERAL PURPOSE COMPUTATION ON GPUS: A PRIMER
Streaming Architectures and Technology Trends
The GeForce 6 Series GPU Architecture
Mapping Computational Concepts to GPUs
GPU Computation Strategies and Tips
Implementing Efficient Parallel Data Structures on GPUs
Flow Control Idioms
GPU Program Optimization
Stream Reduction Operations for GPGPU Applications
PART 5: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 6: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

Excellent Second Book in the GPU Gems Series

This book is the second installment of the GPU Gems book series by NVIDIA. Just like the first book, GPU Gems 2 is a collection of articles by various authors from game development companies, academia, and tool developers on advanced techniques for programming graphics processing units (or GPUs for short). It is aimed at intermediate to advanced graphics developers that are familiar with the most common graphics APIs. The reader should also be proficient in C++. As with the first GPU Gems book, GPU Gems 2 is not for beginners. For professional graphics and game developers, however, it is an excellent collection of interesting techniques, tips, and tricks.

The book is divided into six parts, each dealing with a different aspect of GPU programming. Compared to the first book, more emphasis is put on the quickly evolving area of general-purpose computation on GPUs (also called GPGPU). In particular, the last three of the six parts of the book are about GPGPU and its applications. The first three parts, however, are about real-time computer graphics.

The first part of the book contains 8 chapters on photo-realistic rendering that mostly deal with how to efficiently render a large number of objects in a scene, which is a necessity for rendering convincing natural effects, such as grass or trees. Two chapters in this part of the book discuss geometry instancing and segment buffering, and another chapter focuses on using occlusion queries to implement coherent hierarchical occlusion culling.
Other interesting topics in this part of the book include adaptive tessellation of surfaces on the GPU, displacement mapping - an extension to the popular parallax mapping used in some current games - that allows to render realistic bumps on a simple quad, and terrain rendering with geometry clipmaps.

Part two of the book consisting of 11 chapters deals with shading and lighting. This part contains highly interesting chapters on deferred shading in the game S.T.A.L.K.E.R., and computing irradiance environment maps on the GPU in real-time. Furthermore, this part of the book has chapters on rendering atmospheric scattering, implementing bidirectional texture functions on the GPU, dynamic ambient occlusion culling, water rendering, and using shadow mapping with percentage-closer filtering to achieve soft shadows.

The third part of the book consists of 9 chapters on high-quality rendering. Most chapters in this part deal with implementing high-quality filtering in fragment shaders. For example, there is an interesting chapter on filtered line rendering and another chapter on cubic texture filtering. Finally, a GPU-only implementation of improved Perlin Noise is also presented in this part of the book.

The chapters in the fourth part of the book represent an introduction to the fantastic field of GPGPU. The 8 chapters of this part first describe the general streaming architecture of GPUs, and then move on to show how to map conventional CPU data structures and algorithms to the GPU. For example, textures can be regarded as the GPU equivalent to CPU data arrays. There is also a chapter on how to implement flow-control idioms on the GPU and a chapter on optimizing GPU programs.

The 6 chapters of part five of the book are on image-oriented computing and describe a number of GPGPU algorithms for performing global illumination computations, for example by using radiosity, on the GPU. There is also a chapter on doing computer vision on the GPU
The final chapter in this part of the book explains how to perform conservative rasterization, which is important for some GPGPU algorithms to achieve accurate results.

The final part of the book has 6 chapters that present GPGPU techniques to perform a variety of simulation and numerical algorithms on the GPU. One chapter shows how to map linear algebra operations onto the GPU and develops a GPU framework to solve systems of linear equations. In other chapters the GPU is used for protein structure prediction, options pricing, flow simulation, and medical image reconstruction. These chapters show good examples of how the GPU can be used for non-graphics-related tasks.

The book contains many illustrations and diagrams that visualize the results of certain techniques or explain the presented algorithms in more detail. All images in the book are in color, which is definitely advantageous for a graphics book. In my opinion, the excellent quality and also the quantity of images and illustrations is one of the strongest points of this book compared to other graphics books.

The book also comes with a CD-ROM with supplemental material, videos, and demo applications to some chapters. Most of the applications include the full source code, which makes it easy to experiment with the techniques presented in the book. Note that most of the applications run on Windows only and many of them require a shader model 3.0 graphics card.

I highly recommend this book to any professional working as graphics or game developer. It is a valuable addition to my library of graphics books and I will come back to a number of articles in the near future. The focus on GPGPU in the second half of the book is a welcome addition and we can expect to see more and more non-graphics-related applications make use of the processing power in today’s GPUs.

Pretty pictures

This book is targeted at people who have a good solid grasp of either OpenGL or D3D as well as a grounding in programming languages such as C/C++ or Java. While this much is obvious, the book is still painfully difficult to get anything useful out of.
The problem amounts to the fact that there is no cohesion between chapters - each one is written by a different author (and clearly they have not read each other’s material) - there is no reference or introduction but worst of all, no common terms.
Example; What D3D calls a "pixel shader", OpenGL call "fragment shader", but there are also "vertex shader", "vertex program", "pixel program" and "fragment program"... some of these are the same thing while others are wildly different, but I found at least 4 references in this book to what I could only make sense of by substituting another term (the correct one). Each author has written their part from their own view point using their own terms.
The code snippets contained rarely have any comments or even descriptions of how they work.
Overall I generally felt like I was either reading someone’s thesis or a marketing spiel about a particular aspect of some game.
There are many pretty pictures though.

A Focus on Hardware Optimization

"GPU Gems 2" edited by Matt Pharr (Addison-Wesley, 2005, ISBN 0-321-33559-7) is a collection of forty-eight white papers that detail cutting edge techniques based on today’s latest graphical processing units (GPU). The full color hardcover text is 784 pages and includes a CD-ROM with working demos and source for some of the articles presented in the book. The text retails for $59.99.

The book is divided into six parts: geometric complexity, shading, high-quality rendering, general purpose computation on the GPU, image oriented computing, and numerical algorithms. A part has anywhere from five to twelve chapters. Each chapter is written by a different author but the format and style is consistent. The chapters have an introduction, discussion of the problem or technique, conclusion, and references. The material is presented with color illustrations and occasionally some pseudo-code or code fragments. Generally, the material is extremely current and very approachable to read.

As a sequel to its well received predecessor, the text focuses on taking advantage of the computational power and features of today’s high-powered GPU boards. The first part of the book, geometric complexity, emphasizes this with chapters dedicated to batch rendering, using multi-streaming, hardware occlusion, and displacement pixel-shaders. Each chapter illustrates how operations traditionally performed on the CPU can be moved into the GPU for efficiency and greater effect.

The subsequent two parts on shading and rendering continue along the same theme: improved performance by using hardware functionality found on the GPU. Each topic considers the performance ramifications and GPU capabilities when discussing the problem domain of a rendering technique and factors it into the final solution. For example, chapter 10 considers irradiance environment maps for fast lighting - but with a twist - using the GPU to do the calculations in real-time. In doing so, the book’s real value becomes apparent.

The fourth part on general purpose GPU computation is an interesting addition to the text. The chapters illustrate methods of offloading traditional CPU tasks by exploiting the inherent parallel nature of modern GPU hardware. Since the book features Nvidia hardware, the architecture and performance capabilities largely focused on their products.

In the fifth part of the book, hardware assisted image creation and analysis is considered. By using context clues from the spatial, texture, or lighting data - additional refinements can be made to a scene prior to rasterization. The topics presented in this part are further refinements of the text’s main theme (using the GPU fully) and are specific solutions to uncommon problems - or approaches to rasterization. None the less as GPUs continue to evolve, the topics presented in this section will undoubtedly become more common.

Finally, the sixth part of the book provides several non-traditional graphics examples to illustrate calculating data on the GPU: solving linear equations, options pricing, and numerical simulation - just to name a few. As using the raw floating point power of modern GPU is a growing trend - these sections were quite interesting and well done.

The included CD-ROM contains examples to 28 of the 48 articles in the book. In most cases, the example material includes source code as well as pre-compiled binaries to help illustrate the topic presented in the text. In order to run the majority of the samples, Cg must be installed on the host computer. In addition, the CD-ROM provides access to Nvidia’s software development kit, Cg toolkit, performance tools, and several helpful reference links to on-line sites.

GPU Gems 2 provides a cutting edge view of the capabilities found in today’s video cards. The selected articles illustrate that every part of the rendering process can be enhanced in some fashion by fully using the underlying hardware. As such, this book is essential to anyone working with modern GPUs.

Another magnificent piece of work

The original book was awesome. This book is just as fine of a follow on. The full color on every page, the excellent use of images, and the quality editing all add up to a very fine work indeed. If you loved the second one, buy this one. If high-end 3D graphics are your thing and you haven’t read these books yet, buy both.