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Parallel Computing with C++ and GPUs: Unlock Maximum Performance for Scientific Computing, AI, and Real-Time Systems
Parallel Computing with C++ and GPUs is your direct route to building high-performance applications that power scientific breakthroughs, next-generation AI, and real-time systems. Whether you’re optimizing simulations, accelerating machine learning, or architecting the backbone of modern analytics, this book delivers the hands-on strategies and knowledge you need-without fluff or filler.
At its core, this book shows you how to harness the true potential of GPU hardware with modern C++. It cuts through vendor complexity, equipping you to write portable, robust, and highly optimized code that runs efficiently across NVIDIA, AMD, and Intel platforms.
You’ll master:
Essential GPU fundamentals and C++ toolchains-including CUDA, SYCL, and HIP-for rapid setup and real-world productivity.
Core parallel programming techniques: thread and memory management, efficient data transfer patterns, and kernel optimization.
Portable, production-grade code structures for multi-GPU systems, scalable matrix operations, streaming pipelines, and advanced AI workloads.
Best practices for debugging, testing, continuous integration, and maintaining your code through hardware and toolkit upgrades.
Every chapter is loaded with clear explanations, real working examples, and expert insights that prepare you to deliver results from day one. Topics like memory hierarchy, concurrency with streams, profiling for peak performance, and platform-agnostic CMake templates ensure you’re always a step ahead.
Stop letting hardware limitations define your results. Gain the competitive edge in scientific computing, artificial intelligence, and high-speed applications.
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