This book covers a broad range of topics, from the fundamentals of GPU design to the latest technological trends, but its primary goal is to help software developers gain a deeper understanding of how GPU hardware operates. In recent years, GPUs have become essential tools not only for graphics processing but also for parallel computation, widely used in fields such as deep learning, data analysis, and scientific simulations. To efficiently handle these complex tasks in software, it is crucial to understand the characteristics and design of the underlying hardware.

Many software developers, when first encountering GPU programming, tend to focus solely on API usage or code optimization. However, to fully harness the potential of GPU performance, one must understand the architecture and operational principles of the hardware. Understanding which operations can cause bottlenecks, why memory management is critical, and how thread processing can be optimized opens new avenues for software optimization.

This book delves deeply into GPU architecture and design principles, with the goal of helping developers understand the hardware constraints and how to overcome them. By gaining insight into the inner workings of the GPU, developers will be better equipped to maximize performance in GPU programming.