Advanced CUDA Programming: High Performance Computing with GPUs

Thomas, Gareth Morgan

ISBN 13: 9798310265844

Published by Independently published, 2025

About this Item

Seller Inventory # 49884637-n

Bibliographic Details

• Title: Advanced CUDA Programming: High Performance Computing with GPUs
• Publisher: Independently published
• Publication Date: 2025
• Language: English
• ISBN 13: 9798310265844
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Advanced CUDA Programming: High-Performance Computing with GPUs is the ultimate guide to unlocking the full power of modern GPU computing. Whether you're developing AI models, optimizing scientific simulations, or pushing real-time applications to their limits, this book delivers the advanced techniques and expert insights you need to achieve peak CUDA performance.

GPU programming is no longer optional—it's a necessity in today's world of deep learning, AI acceleration, and high-performance computing. But simply writing CUDA kernels isn’t enough. To truly optimize GPU applications, you need a deep understanding of GPU architecture, memory hierarchies, execution models, and performance tuning strategies. This book takes you beyond the fundamentals and into the world of advanced CUDA programming, where efficiency, scalability, and raw computational power define success.

What You’ll Learn:

• Deep GPU Architecture Insights – Explore the Ampere and Hopper architectures, including streaming multiprocessors, warp scheduling, and memory controller design.
• Memory Optimization Techniques – Implement coalesced memory access, shared memory tuning, cache optimizations, and unified memory strategies for peak performance.
• Asynchronous Execution & CUDA Streams – Master multi-stream processing, event-based synchronization, and pinned memory usage to maximize parallelism.
• High-Performance Kernel Development – Learn thread block optimization, warp-level programming, and dynamic parallelism for efficient kernel execution.
• AI & Deep Learning Acceleration – Optimize GEMM, convolution operations, mixed precision training, and inference using tensor cores.
• Multi-GPU & Distributed Computing – Scale workloads across GPUs with P2P communication, NVLink, workload distribution, and MPI integration.
• Real-Time Processing & Low-Latency Optimization – Develop real-time applications with deterministic execution, deadline scheduling, and pipeline optimizations.
• Debugging & Profiling Mastery – Use Nsight Compute, CUDA-GDB, memory checking tools, and roofline analysis to fine-tune CUDA applications.

Why This Book?

This isn’t just another CUDA guide—it’s a masterclass in performance optimization. Packed with real-world case studies, hands-on techniques, and cutting-edge strategies, it delivers everything you need to develop fast, scalable, and production-ready GPU applications.

If you're ready to take your CUDA skills to the next level and maximize GPU performance like never before, this book is your roadmap. Don't leave performance on the table—start optimizing today.