Book Image

Mastering Graphics Programming with Vulkan

By : Marco Castorina, Gabriel Sassone
5 (2)
Book Image

Mastering Graphics Programming with Vulkan

5 (2)
By: Marco Castorina, Gabriel Sassone

Overview of this book

Vulkan is now an established and flexible multi-platform graphics API. It has been adopted in many industries, including game development, medical imaging, movie productions, and media playback but learning it can be a daunting challenge due to its low-level, complex nature. Mastering Graphics Programming with Vulkan is designed to help you overcome this difficulty, providing a practical approach to learning one of the most advanced graphics APIs. In Mastering Graphics Programming with Vulkan, you’ll focus on building a high-performance rendering engine from the ground up. You’ll explore Vulkan’s advanced features, such as pipeline layouts, resource barriers, and GPU-driven rendering, to automate tedious tasks and create efficient workflows. Additionally, you'll delve into cutting-edge techniques like mesh shaders and real-time ray tracing, elevating your graphics programming to the next level. By the end of this book, you’ll have a thorough understanding of modern rendering engines to confidently handle large-scale projects. Whether you're developing games, simulations, or visual effects, this guide will equip you with the skills and knowledge to harness Vulkan’s full potential.
Table of Contents (21 chapters)
1
Part 1: Foundations of a Modern Rendering Engine
7
Part 2: GPU-Driven Rendering
13
Part 3: Advanced Rendering Techniques

Implementing cloth simulation using async compute

In this section, we are going to implement a simple cloth simulation on the GPU as an example use case of a compute workload. We start by explaining why running some tasks on the GPU might be beneficial. Next, we provide an overview of compute shaders. Finally, we show how to port code from the CPU to the GPU and highlight some of the differences between the two platforms.

Benefits of using compute shaders

In the past, physics simulations mainly ran on the CPU. GPUs only had enough compute capacity for graphics work, and most stages in the pipeline were implemented by dedicated hardware blocks that could only perform one task. As GPUs evolved, pipeline stages moved to generic compute blocks that could perform different tasks.

This increase both in flexibility and compute capacity has allowed engine developers to move some workloads on the GPU. Aside from raw performance, running some computations on the GPU avoids expensive...