Book Image

Mastering Graphics Programming with Vulkan

By : Marco Castorina, Gabriel Sassone
5 (1)
Book Image

Mastering Graphics Programming with Vulkan

5 (1)
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. Learning Vulkan is a foundational step to understanding how a modern graphics API works, both on desktop and mobile. In Mastering Graphics Programming with Vulkan, you’ll begin by developing the foundations of a rendering framework. You’ll learn how to leverage advanced Vulkan features to write a modern rendering engine. The chapters will cover how to automate resource binding and dependencies. You’ll then take advantage of GPU-driven rendering to scale the size of your scenes and finally, you’ll get familiar with ray tracing techniques that will improve the visual quality of your rendered image. By the end of this book, you’ll have a thorough understanding of the inner workings of a modern rendering engine and the graphics techniques employed to achieve state-of-the-art results. The framework developed in this book will be the starting point for all your future experiments.
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

Improving ray-traced shadows

In the previous section, we described a simple algorithm that can be used to compute the visibility term in our scene. As we mentioned, this doesn’t scale well for a large number of lights and can require a large number of samples for different types of light.

In this section, we are going to implement a different algorithm inspired by the article Ray Traced Shadows in the Ray Tracing Gems book. As will be common in this chapter and upcoming chapters, the main idea is to spread the computation cost over time.

This can still lead to noisy results, as we are still using a low number of samples. To achieve the quality we are looking for, we are going to make use of spatial and temporal filtering, similar to what we did in Chapter 11, Temporal Anti-Aliasing.

The technique is implemented over three passes, and we are also going to leverage motion vectors. We are now going to explain each pass in detail.

Motion vectors

As we saw in Chapter...