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GPGPU Programming for Games and Science [Kõva köide]

(Geometric Tools LLC, Redmond, Washington, USA)
  • Formaat: Hardback, 469 pages, kõrgus x laius: 191x235 mm, kaal: 974 g, 26 Tables, black and white; 54 Illustrations, black and white
  • Ilmumisaeg: 15-Aug-2014
  • Kirjastus: A K Peters
  • ISBN-10: 1466595353
  • ISBN-13: 9781466595354
Teised raamatud teemal:
GPGPU Programming for Games and ScienceSuurem pilt
  • Formaat: Hardback, 469 pages, kõrgus x laius: 191x235 mm, kaal: 974 g, 26 Tables, black and white; 54 Illustrations, black and white
  • Ilmumisaeg: 15-Aug-2014
  • Kirjastus: A K Peters
  • ISBN-10: 1466595353
  • ISBN-13: 9781466595354
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781466595354.html
Märksõnad:
An In-Depth, Practical Guide to GPGPU Programming Using Direct3D 11

GPGPU Programming for Games and Science demonstrates how to achieve the following requirements to tackle practical problems in computer science and software engineering:











Robustness Accuracy Speed Quality source code that is easily maintained, reusable, and readable

The book primarily addresses programming on a graphics processing unit (GPU) while covering some material also relevant to programming on a central processing unit (CPU). It discusses many concepts of general purpose GPU (GPGPU) programming and presents practical examples in game programming and scientific programming.

The author first describes numerical issues that arise when computing with floating-point arithmetic, including making trade-offs among robustness, accuracy, and speed. He then shows how single instruction multiple data (SIMD) extensions work on CPUs since GPUs also use SIMD.

The core of the book focuses on the GPU from the perspective of Direct3D 11 (D3D11) and the High Level Shading Language (HLSL). This chapter covers drawing 3D objects; vertex, geometry, pixel, and compute shaders; input and output resources for shaders; copying data between CPU and GPU; configuring two or more GPUs to act as one; and IEEE floating-point support on a GPU.

The book goes on to explore practical matters of programming a GPU, including code sharing among applications and performing basic tasks on the GPU. Focusing on mathematics, it next discusses vector and matrix algebra, rotations and quaternions, and coordinate systems. The final chapter gives several sample GPGPU applications on relatively advanced topics.

Web ResourceAvailable on a supporting website, the authors fully featured Geometric Tools Engine for computing and graphics saves you from having to write a large amount of infrastructure code necessary for even the simplest of applications involving shader programming. The engine provides robust and accurate source code with SIMD when appropriate and GPU versions of algorithms when possible.
List of Figures xiii
List of Tables xv
Listings xvii
Preface xxv
Trademarks xxvii
1 Introduction 1(4)
2 CPU Computing 5(88)
2.1 Numerical Computing
5(9)
2.1.1 The Curse: An Example from Games
5(5)
2.1.2 The Curse: An Example from Science
10(1)
2.1.3 The Need to Understand Floating-Point Systems
11(3)
2.2 Balancing Robustness, Accuracy, and Speed
14(8)
2.2.1 Robustness
14(5)
2.2.1.1 Formal Definitions
14(2)
2.2.1.2 Algorithms and Implementations
16(1)
2.2.1.3 Practical Definitions
17(2)
2.2.2 Accuracy
19(1)
2.2.3 Speed
20(1)
2.2.4 Computer Science Is a Study of Trade-offs
20(2)
2.3 IEEE Floating Point Standard
22(1)
2.4 Binary Scientific Notation
23(8)
2.4.1 Conversion from Rational to Binary Scientific Numbers
24(3)
2.4.2 Arithmetic Properties of Binary Scientific Numbers
27(3)
2.4.2.1 Addition of Binary Scientific Numbers
28(1)
2.4.2.2 Subtraction of Binary Scientific Numbers
28(1)
2.4.2.3 Multiplication of Binary Scientific Numbers
28(1)
2.4.2.4 Division of Binary Scientific Numbers
29(1)
2.4.3 Algebraic Properties of Binary Scientific Numbers
30(1)
2.5 Floating-Point Arithmetic
31(62)
2.5.1 Binary Encodings
32(18)
2.5.1.1 8-bit Floating-Point Numbers
33(3)
2.5.1.2 16-Bit Floating-Point Numbers
36(3)
2.5.1.3 32-Bit Floating-Point Numbers
39(2)
2.5.1.4 64-Bit Floating-Point Numbers
41(1)
2.5.1.5 n-Bit Floating-Point Numbers
42(3)
2.5.1.6 Classifications of Floating-Point Numbers
45(5)
2.5.2 Rounding and Conversions
50(31)
2.5.2.1 Rounding with Ties-to-Even
51(1)
2.5.2.2 Rounding with Ties-to-Away
52(1)
2.5.2.3 Rounding toward Zero
52(1)
2.5.2.4 Rounding toward Positive
52(1)
2.5.2.5 Rounding toward Negative
53(1)
2.5.2.6 Rounding from Floating-Point to Integral Floating-Point
54(6)
2.5.2.7 Conversion from Integer to Floating-Point
60(4)
2.5.2.8 Conversion from Floating-Point to Rational
64(3)
2.5.2.9 Conversion from Rational to Floating-Point
67(3)
2.5.2.10 Conversion to Wider Format
70(3)
2.5.2.11 Conversion to Narrower Format
73(8)
2.5.3 Arithmetic Operations
81(1)
2.5.4 Mathematical Functions
82(1)
2.5.5 Floating-Point Oddities
83(10)
2.5.5.1 Where Have My Digits Gone?
83(5)
2.5.5.2 Have a Nice Stay!
88(1)
2.5.5.3 The Best I Can Do Is That Bad?
89(2)
2.5.5.4 You Have Been More Than Helpful
91(1)
2.5.5.5 Hardware and Optimizing Compiler Issues
92(1)
3 SIMD Computing 93(30)
3.1 Intel Streaming SIMD Extensions
93(13)
3.1.1 Shuffling Components
94(1)
3.1.2 Single-Component versus All-Component Access
95(1)
3.1.3 Load and Store Instructions
95(3)
3.1.4 Logical Instructions
98(1)
3.1.5 Comparison Instructions
99(1)
3.1.6 Arithmetic Instructions
100(1)
3.1.7 Matrix Multiplication and Transpose
100(3)
3.1.8 IEEE Floating-Point Support
103(1)
3.1.9 Keep the Pipeline Running
103(1)
3.1.10 Flattening of Branches
104(2)
3.2 SIMD Wrappers
106(1)
3.3 Function Approximations
107(16)
3.3.1 Minimax Approximations
107(3)
3.3.2 Inverse Square Root Function Using Root Finding
110(1)
3.3.3 Square Root Function
111(3)
3.3.4 Inverse Square Root Using a Minimax Algorithm
114(2)
3.3.5 Sine Function
116(1)
3.3.6 Cosine Function
116(1)
3.3.7 Tangent Function
117(1)
3.3.8 Inverse Sine Function
117(2)
3.3.9 Inverse Cosine Function
119(1)
3.3.10 Inverse Tangent Function
119(1)
3.3.11 Exponential Functions
120(1)
3.3.12 Logarithmic Functions
120(3)
4 GPU Computing 123(100)
4.1 Drawing a 3D Object
123(11)
4.1.1 Model Space
123(1)
4.1.2 World Space
123(1)
4.1.3 View Space
124(1)
4.1.4 Projection Space
125(4)
4.1.5 Window Space
129(1)
4.1.6 Summary of the Transformations
130(1)
4.1.7 Rasterization
131(3)
4.2 High Level Shading Language (HLSL)
134(34)
4.2.1 Vertex and Pixel Shaders
134(4)
4.2.2 Geometry Shaders
138(3)
4.2.3 Compute Shaders
141(3)
4.2.4 Compiling HLSL Shaders
144(16)
4.2.4.1 Compiling the Vertex Coloring Shaders
147(4)
4.2.4.2 Compiling the Texturing Shaders
151(1)
4.2.4.3 Compiling the Billboard Shaders
152(4)
4.2.4.4 Compiling the Gaussian Blurring Shaders
156(4)
4.2.5 Reflecting HLSL Shaders
160(8)
4.3 Devices, Contexts, and Swap Chains
168(5)
4.3.1 Creating a Device and an Immediate Context
168(2)
4.3.2 Creating Swap Chains
170(1)
4.3.3 Creating the Back Buffer
171(2)
4.4 Resources
173(28)
4.4.1 Resource Usage and CPU Access
174(1)
4.4.2 Resource Views
175(3)
4.4.3 Subresources
178(1)
4.4.4 Buffers
179(10)
4.4.4.1 Constant Buffers
181(1)
4.4.4.2 Texture Buffers
181(1)
4.4.4.3 Vertex Buffers
182(2)
4.4.4.4 Index Buffers
184(1)
4.4.4.5 Structured Buffers
184(3)
4.4.4.6 Raw Buffers
187(2)
4.4.4.7 Indirect-Argument Buffers
189(1)
4.4.5 Textures
189(6)
4.4.5.1 1D Textures
192(1)
4.4.5.2 2D Textures
193(1)
4.4.5.3 3D Textures
194(1)
4.4.6 Texture Arrays
195(3)
4.4.6.1 1D Texture Arrays
195(1)
4.4.6.2 2D Texture Arrays
196(1)
4.4.6.3 Cubemap Textures
197(1)
4.4.6.4 Cubemap Texture Arrays
198(1)
4.4.7 Draw Targets
198(3)
4.5 States
201(1)
4.6 Shaders
202(5)
4.6.1 Creating Shaders
202(1)
4.6.2 Vertex, Geometry, and Pixel Shader Execution
202(3)
4.6.3 Compute Shader Execution
205(2)
4.7 Copying Data between CPU and GPU
207(7)
4.7.1 Mapped Writes for Dynamic Update
207(3)
4.7.2 Staging Resources
210(1)
4.7.3 Copy from CPU to GPU
211(1)
4.7.4 Copy from GPU to CPU
212(1)
4.7.5 Copy from GPU to GPU
213(1)
4.8 Multiple GPUs
214(3)
4.8.1 Enumerating the Adapters
214(1)
4.8.2 Copying Data between Multiple GPUs
215(2)
4.9 IEEE Floating-Point on the GPU
217(6)
5 Practical Matters 223(34)
5.1 Engine Design and Architecture
223(9)
5.1.1 A Simple Low-Level D3D11 Application
223(3)
5.1.2 HLSL Compilation in Microsoft Visual Studio
226(1)
5.1.3 Design Goals for the Geometric Tools Engine
227(5)
5.1.3.1 An HLSL Factory
227(1)
5.1.3.2 Resource Bridges
228(2)
5.1.3.3 Visual Effects
230(1)
5.1.3.4 Visual Objects and Scene Graphs
231(1)
5.1.3.5 Cameras
231(1)
5.2 Debugging
232(9)
5.2.1 Debugging on the CPU
232(1)
5.2.2 Debugging on the GPU
233(2)
5.2.3 Be Mindful of Your Surroundings
235(6)
5.2.3.1 An Example of an HLSL Compiler Bug
236(3)
5.2.3.2 An Example of a Programmer Bug
239(2)
5.3 Performance
241(8)
5.3.1 Performance on the CPU
241(2)
5.3.2 Performance on the GPU
243(4)
5.3.3 Performance Guidelines
247(2)
5.4 Code Testing
249(8)
5.4.1 Topics in Code Testing
250(4)
5.4.2 Code Coverage and Unit Testing on the GPU
254(3)
6 Linear and Affine Algebra 257(84)
6.1 Vectors
257(16)
6.1.1 Robust Length and Normalization Computations
258(2)
6.1.2 Orthogonality
260(4)
6.1.2.1 Orthogonality in 2D
260(1)
6.1.2.2 Orthogonality in 3D
261(1)
6.1.2.3 Orthogonality in 4D
262(1)
6.1.2.4 Gram-Schmidt Orthonormalization
263(1)
6.1.3 Orthonormal Sets
264(5)
6.1.3.1 Orthonormal Sets in 2D
265(1)
6.1.3.2 Orthonormal Sets in 3D
265(2)
6.1.3.3 Orthonormal Sets in 4D
267(2)
6.1.4 Barycentric Coordinates
269(1)
6.1.5 Intrinsic Dimensionality
270(3)
6.2 Matrices
273(15)
6.2.1 Matrix Storage and Transform Conventions
274(1)
6.2.2 Base Class Matrix Operations
275(3)
6.2.3 Square Matrix Operations in 2D
278(1)
6.2.4 Square Matrix Operations in 3D
279(2)
6.2.5 Square Matrix Operations in 4D
281(1)
6.2.6 The Laplace Expansion Theorem
282(6)
6.3 Rotations
288(30)
6.3.1 Rotation in 2D
288(1)
6.3.2 Rotation in 3D
289(3)
6.3.3 Rotation in 4D
292(2)
6.3.4 Quaternions
294(11)
6.3.4.1 Algebraic Operations
295(2)
6.3.4.2 Relationship of Quaternions to Rotations
297(2)
6.3.4.3 Spherical Linear Interpolation of Quaternions
299(6)
6.3.5 Euler Angles
305(3)
6.3.5.1 World Coordinates versus Body Coordinates
306(2)
6.3.6 Conversion between Representations
308(10)
6.3.6.1 Quaternion to Matrix
309(1)
6.3.6.2 Matrix to Quaternion
309(2)
6.3.6.3 Axis-Angle to Matrix
311(1)
6.3.6.4 Matrix to Axis-Angle
311(1)
6.3.6.5 Axis-Angle to Quaternion
312(1)
6.3.6.6 Quaternion to Axis-Angle
312(1)
6.3.6.7 Euler Angles to Matrix
313(1)
6.3.6.8 Matrix to Euler Angles
313(4)
6.3.6.9 Euler Angles to and from Quaternion or Axis-Angle
317(1)
6.4 Coordinate Systems
318(23)
6.4.1 Geometry and Affine Algebra
319(3)
6.4.2 Transformations
322(10)
6.4.2.1 Composition of Affine Transformations
322(5)
6.4.2.2 Decomposition of Affine Transformations
327(3)
6.4.2.3 A Simple Transformation Factory
330(2)
6.4.3 Coordinate System Conventions
332(4)
6.4.4 Converting between Coordinate Systems
336(5)
7 Sample Applications 341(88)
7.1 Video Streams
341(5)
7.1.1 The VideoStream Class
341(1)
7.1.2 The VideoStreamManager Class
342(4)
7.2 Root Finding
346(9)
7.2.1 Root Bounding
346(1)
7.2.2 Bisection
347(1)
7.2.3 Newton's Method
348(2)
7.2.4 Exhaustive Evaluation
350(5)
7.2.4.1 CPU Root Finding Using a Single Thread
350(1)
7.2.4.2 CPU Root Finding Using Multiple Threads
351(1)
7.2.4.3 GPU Root Finding
352(3)
7.3 Least Squares Fitting
355(9)
7.3.1 Fit a Line to 2D Points
355(3)
7.3.2 Fit a Plane to 3D Points
358(1)
7.3.3 Orthogonal Regression
359(3)
7.3.3.1 Fitting with Lines
359(2)
7.3.3.2 Fitting with Planes
361(1)
7.3.4 Estimation of Tangent Planes
362(2)
7.4 Partial Sums
364(4)
7.5 All-Pairs Triangle Intersection
368(3)
7.6 Shortest Path in a Weighted Graph
371(6)
7.7 Convolution
377(7)
7.8 Median Filtering
384(8)
7.8.1 Median by Sorting
385(2)
7.8.2 Median of 3 x 3 Using Min-Max Operations
387(2)
7.8.3 Median of 5 x 5 Using Min-Max Operations
389(3)
7.9 Level Surface Extraction
392(6)
7.10 Mass-Spring Systems
398(2)
7.11 Fluid Dynamics
400(29)
7.11.1 Numerical Methods
401(2)
7.11.2 Solving Fluid Flow in 2D
403(13)
7.11.2.1 Initialization of State
405(1)
7.11.2.2 Initialization of External Forces
406(3)
7.11.2.3 Updating the State with Advection
409(1)
7.11.2.4 Applying the State Boundary Conditions
410(3)
7.11.2.5 Computing the Divergence of Velocity
413(1)
7.11.2.6 Solving the Poisson Equation
413(1)
7.11.2.7 Updating the Velocity to Be Divergence Free
414(1)
7.11.2.8 Screen Captures from the Simulation
415(1)
7.11.3 Solving Fluid Flow in 3D
416(13)
7.11.3.1 Initialization of State
418(1)
7.11.3.2 Initialization of External Forces
419(3)
7.11.3.3 Updating the State with Advection
422(2)
7.11.3.4 Applying the State Boundary Conditions
424(1)
7.11.3.5 Computing the Divergence of Velocity
425(1)
7.11.3.6 Solving the Poisson Equation
425(2)
7.11.3.7 Updating the Velocity to Be Divergence Free
427(1)
7.11.3.8 Screen Captures from the Simulation
427(2)
Bibliography 429(6)
Index 435
David H. Eberly