Mastering CUDA C++ Programming: From Fundamentals to Advanced GPU Computing: A Complete Guide for High-Performance Programming, Optimization, and Real-World Applications
About this ebook
Dive into the world of GPU programming and accelerate your applications to new heights!
Are you ready to harness the incredible power of parallel processing? Mastering CUDA C++ Programming is your comprehensive guide to unlocking the full potential of NVIDIA GPUs for general-purpose computing. Whether you're a curious beginner or a seasoned programmer, this book will equip you with the knowledge and skills to write high-performance CUDA C++ applications.
What is CUDA?
CUDA (Compute Unified Device Architecture) is a parallel computing platform and programming model developed by NVIDIA. It allows you to use GPUs for general-purpose processing, accelerating applications in fields like artificial intelligence, scientific computing, and high-performance data processing.
Why Choose This Book?
Crystal-Clear Explanations: Complex concepts are broken down into digestible chunks, with plenty of examples and analogies to aid understanding. Even if you're new to GPU programming or parallel programming, you'll grasp the fundamentals with ease.
Hands-On Learning: Solidify your understanding with practical projects that guide you through building real-world CUDA applications. You'll find CUDA examples throughout the book, illustrating key concepts and techniques.
Optimization Mastery: Master advanced techniques for CUDA optimization, including CUDA streams, shared memory, and dynamic parallelism, to achieve peak performance and efficiency in your code.
Real-World Applications: Explore how CUDA C++ is used in diverse fields, from deep learning and machine learning to scientific computing and image processing. We'll even delve into cutting-edge applications in AI, autonomous systems, and robotics.
Future-Proof Your Skills: Get a glimpse into the future of NVIDIA CUDA and its role in emerging technologies like AI and quantum computing.
What You'll Learn
Fundamentals of CUDA Programming: Understand the basics of CUDA programming with CUDA C++, including GPU architecture, memory management, and thread organization.
CUDA Libraries: Leverage powerful CUDA libraries like cuBLAS and cuFFT to accelerate linear algebra and signal processing tasks.
Streamlining Development with Thrust: Explore the Thrust library to simplify CUDA development and write more concise and efficient code.
Debugging and Profiling: Master debugging techniques and profiling tools to identify and resolve issues in your CUDA code.
Advanced Optimization: Dive deep into advanced optimization techniques, including memory coalescing, warp divergence, and kernel fusion.
Multi-GPU Programming: Learn how to harness the power of multiple GPUs to tackle even larger and more demanding computational challenges.
A Comprehensive Guide for All Levels
This book serves as both a CUDA tutorial for beginners and a comprehensive CUDA guide for experienced programmers. It's your one-stop resource for mastering CUDA C++ and unlocking the incredible power of parallel processing.
Don't miss out on this opportunity to accelerate your applications and become a proficient CUDA C++ programmer!
Order your copy of Mastering CUDA C++ Programming today and start your journey into the world of high-performance computing!
Ratings and reviews
About the author
Toby Webber is a high-performance computing expert and seasoned software engineer specializing in GPU programming and parallel computing. With over 15 years of experience in scientific computing, AI acceleration, and real-time graphics optimization, he has helped engineers and researchers push the boundaries of what’s possible using CUDA C++ and modern GPU architectures.
Toby is known for his clear, structured teaching style and his ability to translate complex computational theories into practical, high-impact solutions. He has led performance-critical projects across industries including finance, autonomous systems, and advanced simulations, and regularly mentors development teams on optimizing code for speed and scalability.
When not writing or consulting, Toby contributes to open-source HPC libraries, speaks at tech conferences, and explores innovations in heterogeneous computing and deep learning acceleration.
