mastering gpu programming cuda von cole ethan (7 Ergebnisse)

Paperback. Zustand: New.

Paperback. Zustand: New.

Paperback. Zustand: New.

Paperback. Zustand: New.

Paperback. Zustand: new. Paperback. Master the full power of GPU acceleration and take your C++ applications to performance levels that CPUs alone simply can't reach.Mastering GPU Programming with C++ and CUDA is a practical, modern, and results-driven guide for developers who want to build lightning-fast parallel applications, optimize CUDA workloads, and even deliver GPU-powered libraries that can be used directly from Python.Whether you're accelerating simulations, processing massive datasets, building real-time applications, or exploring high-performance computing, this book shows you exactly how to harness NVIDIA GPUs with confidence-and produce software that truly scales.Unlock the Real Performance Potential of GPUsStarting from the core principles of parallelism and GPU architecture, you'll learn how to think like a GPU programmer. Step-by-step, you'll write your first kernels, optimize memory usage, scale across multiple GPUs, and leverage advanced features like CUDA streams and asynchronous execution.Build Skills That Translate to Real-World ImpactThrough clear explanations, hands-on examples, and professional optimization techniques, you will learn how to: Develop high-performance parallel applications in C++ and CUDAOptimize kernels, memory transfers, and GPU resource usageAnalyze and eliminate bottlenecks with profiling toolsScale workloads using multi-GPU and distributed modelsPackage GPU-powered code into reusable C++ librariesExpose CUDA libraries to Python using PyBind11 for broader adoptionGo Beyond Tutorials-Build Production-Ready SolutionsThis isn't just a collection of code snippets. You'll explore real engineering practices: Modern C++ patterns for safer GPU resource managementAPI design and modular GPU library architectureDeployment strategies for research, enterprise, and cloud environmentsBest practices for maintainability, testing, and cross-platform buildsExpand Your Reach with Python IntegrationWith Python now dominating AI, data science, and research, the book teaches you how to connect your GPU-accelerated C++ code to Python-turning your work into reusable, scalable, and widely adoptable tools.Who This Book Is ForC++ developers breaking into GPU computingEngineers and researchers building high-performance applicationsProfessionals working in AI, simulation, finance, analytics, robotics, gaming, and scientific computingAnyone who wants to unlock more speed, scalability, and efficiency from their softwareNo prior CUDA experience is required just solid C++ fundamentals and the desire to push performance boundaries.Why This Book Stands OutUnlike generic CUDA resources, this book: Covers fundamentals and advanced optimizationBridges C++ and Python for maximum versatilityFocuses on reusable, production-grade techniquesPrepares you for the fast-evolving GPU landscape, cloud platforms, and next-gen hardware This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Zustand: New. Print on Demand.

Paperback. Zustand: new. Paperback. Master the full power of GPU acceleration and take your C++ applications to performance levels that CPUs alone simply can't reach.Mastering GPU Programming with C++ and CUDA is a practical, modern, and results-driven guide for developers who want to build lightning-fast parallel applications, optimize CUDA workloads, and even deliver GPU-powered libraries that can be used directly from Python.Whether you're accelerating simulations, processing massive datasets, building real-time applications, or exploring high-performance computing, this book shows you exactly how to harness NVIDIA GPUs with confidence-and produce software that truly scales.Unlock the Real Performance Potential of GPUsStarting from the core principles of parallelism and GPU architecture, you'll learn how to think like a GPU programmer. Step-by-step, you'll write your first kernels, optimize memory usage, scale across multiple GPUs, and leverage advanced features like CUDA streams and asynchronous execution.Build Skills That Translate to Real-World ImpactThrough clear explanations, hands-on examples, and professional optimization techniques, you will learn how to: Develop high-performance parallel applications in C++ and CUDAOptimize kernels, memory transfers, and GPU resource usageAnalyze and eliminate bottlenecks with profiling toolsScale workloads using multi-GPU and distributed modelsPackage GPU-powered code into reusable C++ librariesExpose CUDA libraries to Python using PyBind11 for broader adoptionGo Beyond Tutorials-Build Production-Ready SolutionsThis isn't just a collection of code snippets. You'll explore real engineering practices: Modern C++ patterns for safer GPU resource managementAPI design and modular GPU library architectureDeployment strategies for research, enterprise, and cloud environmentsBest practices for maintainability, testing, and cross-platform buildsExpand Your Reach with Python IntegrationWith Python now dominating AI, data science, and research, the book teaches you how to connect your GPU-accelerated C++ code to Python-turning your work into reusable, scalable, and widely adoptable tools.Who This Book Is ForC++ developers breaking into GPU computingEngineers and researchers building high-performance applicationsProfessionals working in AI, simulation, finance, analytics, robotics, gaming, and scientific computingAnyone who wants to unlock more speed, scalability, and efficiency from their softwareNo prior CUDA experience is required just solid C++ fundamentals and the desire to push performance boundaries.Why This Book Stands OutUnlike generic CUDA resources, this book: Covers fundamentals and advanced optimizationBridges C++ and Python for maximum versatilityFocuses on reusable, production-grade techniquesPrepares you for the fast-evolving GPU landscape, cloud platforms, and next-gen hardware This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.