Maris fenlor (15 risultati)
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Da: BargainBookStores, Grand Rapids, U.S.A.BargainBookStores
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EUR 46,48
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Paperback or Softback. Condizione: New. Practical GPU Programming: High-performance computing with CUDA, CuPy, and Python on modern GPUs. Book.
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Da: Rarewaves USA, OSWEGO, U.S.A.Rarewaves USA
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EUR 50,54
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Paperback. Condizione: New.
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Da: California Books, Miami, U.S.A.California Books
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Da: Rarewaves.com USA, London, Regno UnitoRarewaves.com USA
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EUR 54,34
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Paperback. Condizione: New.
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Da: Rarewaves USA United, OSWEGO, U.S.A.Rarewaves USA United
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EUR 54,74
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Paperback. Condizione: New.
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Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
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EUR 75,26 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Paperback. Condizione: New.
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Da: PBShop.store US, Wood Dale, U.S.A.PBShop.store US
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EUR 60,48
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PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Da: PBShop.store UK, Fairford, Regno UnitoPBShop.store UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 58,10
EUR 3,81 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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EUR 74,48
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Condizione: New. Print on Demand.
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Da: Books Puddle, New York, U.S.A.Books Puddle
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EUR 80,80
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Condizione: New. Print on Demand.
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Da: Biblios, frankfurt am main, GermaniaBiblios
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EUR 75,31
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 63,90
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 130 pp. Englisch.
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Da: buchversandmimpf2000, Emtmannsberg, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 63,90
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -If you're a Python pro looking to get the most out of your code with GPUs, then Practical GPU Programming is the right book for you. This book will walk you through the basics of GPU architectures, show you hands-on parallel programmin…g techniques, and give you the know-how to confidently speed up real workloads in data processing, analytics, and engineering.The first thing you'll do is set up the environment, install CUDA, and get a handle on using Python libraries like PyCUDA and CuPy. You'll then dive into memory management, kernel execution, and parallel patterns like reductions and histogram computations. Then, we'll dive into sorting and search techniques, but with a focus on how GPU acceleration transforms business data processing. We'll also put a strong emphasis on linear algebra to show you how to supercharge classic vector and matrix operations with cuBLAS and CuPy. Plus, with batched computations, efficient broadcasting, custom kernels, and mixed-library workflows, you can tackle both standard and advanced problems with ease.Throughout, we evaluate numerical accuracy and performance side by side, so you can understand both the strengths and limitations of GPU-based solutions. The book covers nearly every essential skill and modern toolkit for practical GPU programming, but it's not going to turn you into a master overnight.Key LearningsBoost processing speed and efficiency for data-intensive tasks.Use CuPy and PyCUDA to write and execute custom CUDA kernels.Maximize GPU occupancy and throughput efficiency by using optimal thread block and grid configuration.Reduce global memory bottlenecks in kernels by using shared memory and coalesced access patterns.Perform dynamic kernel compilation to ensure tailored performance.Use CuPy to carry out custom, high-speed elementwise GPU operations and expressions.Implement bitonic and radix sort algorithms for large or batch integer datasets.Execute parallel linear search kernels to detect patterns rapidly.Scale matrix operations using Batched GEMM and high-level cuBLAS routines.Table of ContentIntroduction to GPU FundamentalsSetting up GPU Programming EnvironmentBasic Data Transfers and Memory TypesSimple Parallel PatternsIntroduction to Kernel OptimizationWorking with PyCUDA and CuPy FeaturesPractical Sorting and SearchLinear Algebra Essentials on GPULibri GmbH, Europaallee 1, 36244 Bad Hersfeld 130 pp. Englisch.
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Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 61,20
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: Neu. Practical GPU Programming | High-performance computing with CUDA, CuPy, and Python on modern GPUs | Maris Fenlor | Taschenbuch | Englisch | 2025 | GitforGits | EAN 9789349174795 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preig…u Print on Demand.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 71,51
EUR 61,30 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - If you're a Python pro looking to get the most out of your code with GPUs, then Practical GPU Programming is the right book for you. This book will walk you through the basics of GPU architectures, show you hands-on parallel programming… techniques, and give you the know-how to confidently speed up real workloads in data processing, analytics, and engineering.The first thing you'll do is set up the environment, install CUDA, and get a handle on using Python libraries like PyCUDA and CuPy. You'll then dive into memory management, kernel execution, and parallel patterns like reductions and histogram computations. Then, we'll dive into sorting and search techniques, but with a focus on how GPU acceleration transforms business data processing. We'll also put a strong emphasis on linear algebra to show you how to supercharge classic vector and matrix operations with cuBLAS and CuPy. Plus, with batched computations, efficient broadcasting, custom kernels, and mixed-library workflows, you can tackle both standard and advanced problems with ease.Throughout, we evaluate numerical accuracy and performance side by side, so you can understand both the strengths and limitations of GPU-based solutions. The book covers nearly every essential skill and modern toolkit for practical GPU programming, but it's not going to turn you into a master overnight.Key LearningsBoost processing speed and efficiency for data-intensive tasks.Use CuPy and PyCUDA to write and execute custom CUDA kernels.Maximize GPU occupancy and throughput efficiency by using optimal thread block and grid configuration.Reduce global memory bottlenecks in kernels by using shared memory and coalesced access patterns.Perform dynamic kernel compilation to ensure tailored performance.Use CuPy to carry out custom, high-speed elementwise GPU operations and expressions.Implement bitonic and radix sort algorithms for large or batch integer datasets.Execute parallel linear search kernels to detect patterns rapidly.Scale matrix operations using Batched GEMM and high-level cuBLAS routines.Table of ContentIntroduction to GPU FundamentalsSetting up GPU Programming EnvironmentBasic Data Transfers and Memory TypesSimple Parallel PatternsIntroduction to Kernel OptimizationWorking with PyCUDA and CuPy FeaturesPractical Sorting and SearchLinear Algebra Essentials on GPU.
