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

Summary

In this chapter, we have built the foundations to support compute shaders in our renderer. We started by introducing timeline semaphores and how they can be used to replace multiple semaphores and fences. We have shown how to wait for a timeline semaphore on the CPU and how a timeline semaphore can be used as part of a queue submission, either for it to be signaled or to be waited on.

Next, we demonstrated how to use the newly introduced timeline semaphore to synchronize execution across the graphics and compute queue.

In the last section, we showed an example of how to approach porting code written for the CPU to the GPU. We first explained some of the benefits of running computations on the GPU. Next, we gave an overview of the execution model for compute shaders and the configuration of local and global workgroup sizes. Finally, we gave a concrete example of a compute shader for cloth simulation and highlighted the main differences with the same code written for the...