GPGPU Programming for Games and Science
Год: 2014
Автор: David H. Eberly
Жанр: Программирование
Издательство: A K Peters/CRC Press
ISBN: 978-1466595354
Язык: Английский
Формат: PDF
Качество: Изначально компьютерное (eBook)
Интерактивное оглавление: Да
Количество страниц: 469
Описание: 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 Resource
Available on a supporting website, the author’s 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.
Оглавление
Table of Contents
Introduction
CPU Computing
Numerical Computing
Balancing Robustness, Accuracy, and Speed
IEEE Floating Point Standard
Binary Scientific Notation
Floating-Point Arithmetic
SIMD Computing
Intel Streaming SIMD Extensions
SIMD Wrappers
Function Approximations
GPU Computing
Drawing a 3D Object
High Level Shading Language (HLSL)
Devices, Contexts, and Swap Chains
Resources
States
Shaders
Copying Data between CPU and GPU
Multiple GPUs
IEEE Floating-Point on the GPU
Practical Matters
Engine Design and Architecture
Debugging
Performance
Code Testing
Linear and Affine Algebra
Vectors
Matrices
Rotations
Coordinate Systems
Sample Applications
Video Streams
Root Finding
Least Squares Fitting
Partial Sums
All-Pairs Triangle Intersection
Shortest Path in a Weighted Graph
Convolution
Median Filtering
Level Surface Extraction
Mass-Spring Systems
Fluid Dynamics
Bibliography
