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The C++ Programmer's Mindset

The C++ Programmer's Mindset

By : Sam Morley
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The C++ Programmer's Mindset

The C++ Programmer's Mindset

By: Sam Morley

Overview of this book

Solve complex problems in C++ by learning how to think like a computer scientist. This book introduces computational thinking—a framework for solving problems using decomposition, abstraction, and pattern recognition—and shows you how to apply it using modern C++ features. You'll learn how to break down challenges, choose the right abstractions, and build solutions that are both maintainable and efficient. Through small examples and a large case study, this book guides you from foundational concepts to high-performance applications. You’ll explore reusable templates, algorithms, modularity, and even parallel computing and GPU acceleration. With each chapter, you’ll not only expand your C++ skillset, but also refine the way you approach and solve real-world problems. Written by a seasoned research engineer and C++ developer, this book combines practical insight with academic rigor. Whether you're designing algorithms or profiling production code, this book helps you deliver elegant, effective solutions with confidence.
Table of Contents (19 chapters)
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18
Index

Writing algorithms for GPU using CUDA C++

One of the hardest parts of learning to program GPUs is the massively parallel model of computation. This is radically different from the programming we’re used to on CPUs. One must think about the distribution of work up front and how to organize data movement between different elements of the kernel. Once you get used to some of these concepts, then some of the quirks of the architecture start to become apparent (usually once one starts to profile your kernels). This is not going to be a comprehensive introduction to CUDA programming, but it should give enough to get you started.

The first thing we want to do is define a kernel. A CUDA kernel is defined using the __global__ attribute applied to a function that returns void. There are, of course, restrictions on the arguments that can be passed to a kernel (since these must be copied over to the GPU). We cannot pass data by reference, and any pointer values we pass should point...

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