Randall S Mccarthy (5 results)

Language: English
Published by Salvation Of Souls Publishing Committee Sep 2026, 2026
- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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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.…

Language: English
Published by Independently Published, 2026
- Softcover
- Print on Demand
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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US$ 56.01
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Paperback. Condition: new. Paperback. 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Language: English
Published by Independently published, 2026
- Softcover
- Print on Demand
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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US$ 56.02
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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Language: English
Published by Independently published, 2026
- Softcover
- Print on Demand
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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US$ 47.33
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PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Language: English
Published by Independently Published, 2026
- Softcover
- Print on Demand
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
Contact seller5-star sellerCondition: New
US$ 53.06
US$ 48.89 shippingShips from United Kingdom to U.S.A.Quantity: 1 available
Paperback. Condition: new. Paperback. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…