Practical Gpu Graphics With Wgpu Py And Python
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Practical GPU Graphics with wgpu-py and Python
Wgpu-py is the next-generation Python graphics API and future standard for both native devices and the web, aiming to provide modern 3D graphics and computation capabilities with the GPU acceleration. This book provides all the tools you need to help you create advanced 3D graphics and GPU computing on native devices with this new wgpu-py API. The book starts by taking you through the wgpu-py development environment for building the wgpu-py apps and then shows you the Python and wgpu-py basics, shader programs, GPU buffers, and rendering pipelines. Next, you will learn how to create primitives and simple objects in wgpu-py. As you progress through the chapters, you will get to grips with advanced wgpu-py topics, including 3D transformation, lighting calculation, colormaps, and textures. At the same time, you will learn how to create advanced 3D wgpu-py objects, including various 3D wireframes, 3D shapes, simple and parametric 3D surfaces with colormaps and textures, as well as beautiful fractal images described by complex functions. You will also explore new wgpu features, such as compute shader and storage buffer, and how to use them to simulate large particle systems. In addition, this book will introduce the pygfx render engine that is based on wgpu-py, and show you how to use its built-in primitives to create various 3D objects. You will also learn how to build custom objects and geometries in pygfx. By the end of this book, you will have the skill you need to build your own GPU-accelerated graphics and computing on both native devices and the web with the wgpu-py API.
Practical GPU Graphics with wgpu and Rust
wgpu is the next-generation graphics API and future standard in Rust for both native devices and the web, aiming to provide modern 3D graphics and computation capabilities using GPU acceleration. This book provides all the tools you need to create advanced 3D graphics and GPU computing in Rust using this new wgpu API. First, this book will take you through the development environment for building wgpu applications in Rust, and then introduce Rust and wgpu basics, shader programs, GPU buffers, and rendering pipelines. Next, you will learn how to create primitives and simple objects in wgpu. As you progress through the chapters, you will get to grips with advanced wgpu topics, including 3D transformations, lighting calculations, colormaps, and textures. At the same time, you will learn how to create advanced 3D wgpu objects, including various 3D wireframes, 3D shapes, and simple and parametric 3D surfaces with colormaps and textures, as well as beautiful 2D and 3D fractal images described by complex functions. In addition, you will explore new wgpu features such as the compute shader and storage buffers, and use them to simulate large particle systems. By the end of this book, you will have the solid skills you need to build your own GPU-accelerated graphics and computing applications on both native devices and the web in Rust with the wgpu API. This book includes: - Development environment and tools for building wgpu apps in Rust. - Rust and wgpu basics, WGSL shaders, and rendering pipeline. - Primitives and simple shapes in wgpu. - 3D transformations, model, viewing, projection, and various coordinate systems. - GPU buffers, uniform buffer objects, animation, and camera controls. - Normal vectors, lighting model, ambient, diffuse, and specular light calculations. - UV coordinates, texture mapping. - Color model, colormaps, and color interpolation. - 3D shapes, wireframes, surfaces, and 3D charts. - 2D and 3D fractal images created in the fragment shader. - Compute shaders, storage buffers, and large particle system simulation.
Practical GPU Programming
If you're a Python pro looking to get the most out of your code with GPUs, then Practical GPU Programming is the right book for you. This book will walk you through the basics of GPU architectures, show you hands-on parallel programming techniques, and give you the know-how to confidently speed up real workloads in data processing, analytics, and engineering. The first thing you'll do is set up the environment, install CUDA, and get a handle on using Python libraries like PyCUDA and CuPy. You'll then dive into memory management, kernel execution, and parallel patterns like reductions and histogram computations. Then, we'll dive into sorting and search techniques, but with a focus on how GPU acceleration transforms business data processing. We'll also put a strong emphasis on linear algebra to show you how to supercharge classic vector and matrix operations with cuBLAS and CuPy. Plus, with batched computations, efficient broadcasting, custom kernels, and mixed-library workflows, you can tackle both standard and advanced problems with ease. Throughout, we evaluate numerical accuracy and performance side by side, so you can understand both the strengths and limitations of GPU-based solutions. The book covers nearly every essential skill and modern toolkit for practical GPU programming, but it's not going to turn you into a master overnight. Key Learnings Boost processing speed and efficiency for data-intensive tasks. Use CuPy and PyCUDA to write and execute custom CUDA kernels. Maximize GPU occupancy and throughput efficiency by using optimal thread block and grid configuration. Reduce global memory bottlenecks in kernels by using shared memory and coalesced access patterns. Perform dynamic kernel compilation to ensure tailored performance. Use CuPy to carry out custom, high-speed elementwise GPU operations and expressions. Implement bitonic and radix sort algorithms for large or batch integer datasets. Execute parallel linear search kernels to detect patterns rapidly. Scale matrix operations using Batched GEMM and high-level cuBLAS routines. Table of Content Introduction to GPU Fundamentals Setting up GPU Programming Environment Basic Data Transfers and Memory Types Simple Parallel Patterns Introduction to Kernel Optimization Working with PyCUDA and CuPy Features Practical Sorting and Search Linear Algebra Essentials on GPU