Modern CUDA C++ for Parallel Programming: A Practical Guide to GPU Programming and Building Scalable Kernels for LLMs, Transformers, and Generative AI

$26.99
by Frank Babbit

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The future of GPU computing is no longer about faster chips—it’s about rethinking how we build parallel systems. Modern CUDA C++ for Parallel Computing takes you inside the architecture, tooling, and engineering mindset behind today’s most advanced AI workloads. From Blackwell-era GPUs to next-generation CUDA programming models, this book shows you how to design high-performance kernels that power large language models, transformers, and real-time AI systems. Rather than focusing on theory alone, this guide bridges the gap between hardware evolution and practical implementation—helping you write code that aligns with how modern GPUs actually execute. Written in a clear and direct style, Modern CUDA C++ for Parallel Computing focuses on practical understanding, not unnecessary complexity—giving you the tools to think like a performance engineer and build systems that scale. What you’ll learn • How modern GPU architectures (Blackwell and beyond) reshape parallel programming • Techniques for writing high-throughput CUDA kernels for AI workloads • Efficient memory orchestration using HBM, L2 cache, and emerging memory tiers • Advanced execution models including tile-based programming and cooperative groups • Practical optimization strategies for LLMs, transformers, and generative AI pipelines • How to profile, debug, and eliminate performance bottlenecks using modern tooling What sets this book apart This is not a beginner’s introduction. It’s a performance-oriented guide designed to help you think like a systems engineer. The focus is on how things actually work under the hood—and how to use that knowledge to build faster, more scalable systems. Every concept is grounded in real-world patterns used in modern AI infrastructure, from kernel fusion to memory locality optimization. Who this book is for • Software engineers and backend developers moving into GPU computing • Machine learning engineers optimizing model performance • Systems engineers building scalable AI infrastructure • Experienced developers looking to master modern CUDA C++ If you want to understand not just how CUDA works—but how modern AI systems are actually built on top of it—this book gives you the blueprint. Build faster. Scale further. Write CUDA like a performance engineer.

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