David H. Eberly - Böcker

Create physically realistic 3D Graphics environments with this introduction to the ideas and techniques behind the process. Author David H. Eberly includes simulations to introduce the key problems involved and then gradually reveals the mathematical and physical concepts needed to solve them. He then describes all the algorithmic foundations and uses code examples and working source code to show how they are implemented, culminating in a large collection of physical simulations. The book tackles the complex, challenging issues that other books avoid, including Lagrangian dynamics, rigid body dynamics, impulse methods, resting contact, linear complementarity problems, deformable bodies, mass-spring systems, friction, numerical solution of differential equations, numerical stability and its relationship to physical stability, and Verlet integration methods. This book even describes when real physics isn't necessary - and hacked physics will do.

An In-Depth, Practical Guide to GPGPU Programming Using Direct3D 11GPGPU Programming for Games and Science demonstrates how to achieve the following requirements to tackle practical problems in computer science and software engineering: RobustnessAccuracySpeedQuality 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 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.

An In-Depth, Practical Guide to GPGPU Programming Using Direct3D 11GPGPU Programming for Games and Science demonstrates how to achieve the following requirements to tackle practical problems in computer science and software engineering: RobustnessAccuracySpeedQuality source code that is easily maintained, reusable, and readableThe 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 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.