Isbn: 9798254917564 - mastering cuda 13 with python: gpu programming, ai acceleration, and high-performance computing with pytorch, cupy, numba, and cuda.core: 7 (electrical engineering and programming books) (7 resultados)

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  • Idioma: Inglés

    Editorial: Independently Published, 2026

    9798254917564

    Serie: Libro 5 de 7 - electrical engineering and programming books

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    Idioma: Inglés

    Editorial: Independently Published, 2026

    9798254917564

    Serie: Libro 5 de 7 - electrical engineering and programming books

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    Editorial: Independently Published, 2026

    9798254917564

    Serie: Libro 5 de 7 - electrical engineering and programming books

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    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

    Editorial: Independently Published, 2026

    9798254917564

    Serie: Libro 5 de 7 - electrical engineering and programming books

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    Editorial: Independently published, 2026

    9798254917564

    Serie: Libro 5 de 7 - electrical engineering and programming books

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    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

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  • Idioma: Inglés

    Editorial: Independently Published, 2026

    9798254917564

    Serie: Libro 5 de 7 - electrical engineering and programming books

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    Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail

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    Paperback. Condición: new. Paperback. Are you looking to move beyond CPU limitations and take full advantage of GPU acceleration using Python? Have you ever wondered how modern systems handle massive data processing, complex simulations, or large-scale machine learning tasks efficiently?This book is written to answer those questions with clarity and precision.Mastering CUDA 13 with Python: GPU Programming, AI Acceleration, and High-Performance Computing provides a practical, in-depth guide to building high-performance applications using GPU computing. It focuses on how Python can be used as a powerful interface for developing efficient parallel programs, handling large datasets, and accelerating computation-heavy workloads.Instead of abstract explanations, the book walks through real implementation strategies-covering memory management, kernel design, parallel algorithms, and performance tuning. It explains how to write efficient GPU code, how to avoid common bottlenecks, and how to scale applications across multiple devices. You will also learn how to integrate GPU workflows into data analysis pipelines and machine learning systems without unnecessary complexity.Are you working with large datasets that take too long to process? Trying to train models faster or optimize computational performance? Or looking to understand how modern high-performance systems are built?This book is structured to guide you from foundational concepts to advanced techniques, with a strong focus on practical application. Each chapter builds technical depth, helping you not just use GPU acceleration, but understand how and why it works.If your goal is to write faster, more efficient Python code that fully utilizes modern hardware, this book gives you the knowledge and structure to do it with confidence. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

  • Idioma: Inglés

    Editorial: Independently Published, 2026

    9798254917564

    Serie: Libro 5 de 7 - electrical engineering and programming books

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    Paperback. Condición: new. Paperback. Are you looking to move beyond CPU limitations and take full advantage of GPU acceleration using Python? Have you ever wondered how modern systems handle massive data processing, complex simulations, or large-scale machine learning tasks efficiently?This book is written to answer those questions with clarity and precision.Mastering CUDA 13 with Python: GPU Programming, AI Acceleration, and High-Performance Computing provides a practical, in-depth guide to building high-performance applications using GPU computing. It focuses on how Python can be used as a powerful interface for developing efficient parallel programs, handling large datasets, and accelerating computation-heavy workloads.Instead of abstract explanations, the book walks through real implementation strategies-covering memory management, kernel design, parallel algorithms, and performance tuning. It explains how to write efficient GPU code, how to avoid common bottlenecks, and how to scale applications across multiple devices. You will also learn how to integrate GPU workflows into data analysis pipelines and machine learning systems without unnecessary complexity.Are you working with large datasets that take too long to process? Trying to train models faster or optimize computational performance? Or looking to understand how modern high-performance systems are built?This book is structured to guide you from foundational concepts to advanced techniques, with a strong focus on practical application. Each chapter builds technical depth, helping you not just use GPU acceleration, but understand how and why it works.If your goal is to write faster, more efficient Python code that fully utilizes modern hardware, this book gives you the knowledge and structure to do it with confidence. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…