Mastering GPU Programming with Python and CUDA 13.3: A Practical Guide to Parallel Computing, GPU Kernels, Memory Optimization, Performance Engineering, and Accelerated Applications - Couverture souple

McCarthy, Randall S.

Couverture souple

ISBN 13 : 9798175646819

Editeur : Independently published, 2026

Synopsis

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.

Détails de l'édition

• Éditeur: Independently published
• Date d'édition: 2026
• Langue: anglais
• ISBN 13: 9798175646819
• Reliure: Broché
• Nombre de pages: 586
• Coordonnées du fabricant: Printed by Amazon on behalf of the author; https://www.amazon.fr/hz/contact-us; ; c/o Amazon Media EU S.à.r.l., 38 Avenue John F. Kennedy; Luxembourg; L-1855; Luxembourg