Gpu Computing Applications (61 results)

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Paperback or Softback. Condition: New. GPU-Accelerated Computing with Python 3 and CUDA: From low-level kernels to real-world applications in scientific computing and machine learning. Book.

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Taschenbuch. Condition: Neu. Neuware - Modern applications increasingly require massive amounts of computational power. GPU programming provides a powerful way to accelerate demanding workloads through parallel processing. \*\*Modern GPU Programming with C++ and CUDA from Scratch\*\* offers a practical, beginner-friendly introduction to GPU programming with modern C++ and NVIDIA CUDA. Inside, you'll learn how to: \* Understand parallel computing and GPU architecture\* Set up a CUDA development environment\* Write and execute CUDA kernels\* Work with threads, blocks, grids, and GPU memory\* Build parallel algorithms with C++\* Use shared memory and asynchronous execution\* Profile and optimize GPU applications\* Identify and improve performance bottlenecks\* Understand multi-GPU programming>Whether you're a C++ developer, software engineer, AI practitioner, researcher, or aspiring GPU programmer, this book provides a practical foundation for getting started with CUDA and high-performance computing. By the end, you'll understand the core principles of GPU programming and have the skills needed to begin building and optimizing your own CUDA applications. \*\*Learn parallel computing. Harness GPU power. Build high-performance applications.\*\*.…

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Taschenbuch. Condition: Neu. Neuware - Are you looking to understand modern high-performance computing and get more from your C++ and GPU programming skills C++26 and CUDA 13.3 Performance Engineering offers a practical introduction to parallel computing, GPU programming, kernel development, memory optimization, and performance-focused application design. Whether you're exploring GPU acceleration for the first time or looking to improve existing programming techniques, this guide presents complex ideas in a clear and approachable way.How can you write more efficient code How do GPUs handle demanding workloads What techniques can help reduce unnecessary computation and improve application performance Explore these questions and more through a focused guide designed for programmers, students, developers, and computing enthusiasts interested in building a stronger understanding of performance engineering and modern parallel applications.…

Taschenbuch. Condition: Neu. Neuware - What if your Python programs could handle demanding computational tasks more efficiently Mastering GPU Programming with Python and CUDA 13.3 offers a practical introduction to GPU-based computing and the techniques used to build and optimize accelerated applications. Instead of focusing only on theory, this guide helps you understand the principles behind parallel execution, GPU kernels, memory usage, and performance optimization. How do GPU programs work Which tasks benefit from parallel execution How can memory access affect performance And what techniques can help you identify and improve computational bottlenecks You'll explore these questions through practical discussions of parallel programming, kernel design, memory management, data movement, performance analysis, and application optimization. The book is designed to help readers develop a clearer understanding of how computational workloads can be structured for accelerated hardware. Whether you are building your programming foundation or expanding your knowledge of high-performance computing, this guide provides a structured path toward understanding GPU-based application development and performance engineering.…

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Softcover/Taschenbuch. Condition: Neu. Write efficient GPU-accelerated Python code using CUDA and modern Python libraries. Sprache: Englisch Gewicht in Gramm: 985.

Gebundene Ausgabe. Condition: Neu. Neu Neuware, Importqualität, auf Lager, Sofortversand - GPU Computing Gems, Jade Edition, offers hands-on, proven techniques for general purpose GPU programming based on the successful application experiences of leading researchers and developers. One of few resources available that distills the best practices of the community of CUDA programmers, this second edition contains 100% new material of interest across industry, including finance, medicine, imaging, engineering, gaming, environmental science, and green computing. It covers new tools and frameworks for productive GPU computing application development and provides immediate benefit to researchers developing improved programming environments for GPUs. Divided into five sections, this book explains how GPU execution is achieved with algorithm implementation techniques and approaches to data structure layout. More specifically, it considers three general requirements: high level of parallelism, coherent memory access by threads within warps, and coherent control flow within warps. Chapters explore topics such as accelerating database searches; how to leverage the Fermi GPU architecture to further accelerate prefix operations; and GPU implementation of hash tables. There are also discussions on the state of GPU computing in interactive physics and artificial intelligence; programming tools and techniques for GPU computing; and the edge and node parallelism approach for computing graph centrality metrics. In addition, the book proposes an alternative approach that balances computation regardless of node degree variance. Software engineers, programmers, hardware engineers, and advanced students will find this book extremely usefull. For useful source codes discussed throughout the book, the editors invite readers to the following website: GPU Computing Gems offers 100% new material of interest across industry, including finance, medicine, imaging, engineering, gaming, environmental science, green computing, and more Covers new tools and frameworks for productive GPU computing application development and offers immediate benefit to researchers developing improved programming environments for GPUs Even more hands-on, proven techniques demonstrating how general purpose GPU computing is changing scientific research Distills the best practices of the community of CUDA programmers; each chapter provides insights and ideas as well as 'hands on' skills applicable to a variety of fields.…