Name: GPU Programming with CUDA For Beginners: A Practical Guide to CUDA Programming, GPU Kernels, Memory Management, and Parallel Computing (CUDA Programming Series)
SKU: 68922699
Price: 804.00 TWD
Availability: InStock
Author: Marsh, Alvin
ISBN: 9798171905576

portada GPU Programming with CUDA For Beginners: A Practical Guide to CUDA Programming, GPU Kernels, Memory Management, and Parallel Computing (CUDA Programming Series)

GPU Programming with CUDA For Beginners: A Practical Guide to CUDA Programming, GPU Kernels, Memory Management, and Parallel Computing (CUDA Programming Series)

Type

Physical Book

Publisher

Independently published

Author

Marsh, Alvin

Format

Paperback

ISBN13

9798171905576

GPU Programming with CUDA For Beginners: A Practical Guide to CUDA Programming, GPU Kernels, Memory Management, and Parallel Computing (CUDA Programming Series)

Marsh, Alvin (Author) · Independently published · Paperback

New Book Imported to Taiwan

Delivery: 18 Nov - 26 Nov

NT$ 804

NT$ 804

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Synopsis "GPU Programming with CUDA For Beginners: A Practical Guide to CUDA Programming, GPU Kernels, Memory Management, and Parallel Computing (CUDA Programming Series)"

GPU's have become an important part of modern computing, enabling applications to process large amounts of data through massive parallelism. CUDA provides developers with a powerful programming model for taking advantage of NVIDIA GPUs, but getting started can be challenging when concepts such as kernels, threads, blocks, grids, memory spaces, and synchronization are introduced all at once. GPU Programming with CUDA For Beginners provides a practical introduction to CUDA programming for readers who want to understand how GPU computing works and learn how to build CUDA applications from the ground up. Starting with the fundamentals of GPU architecture and parallel computing, the book progressively introduces the CUDA programming model, kernel execution, threads, thread blocks, grids, memory management, data transfer, synchronization, and common parallel programming patterns. Practical examples help connect these concepts to the way CUDA programs actually execute on a GPU. You will explore how to: Understand the fundamentals of GPU computing and parallel execution Set up a CUDA development environment Write and launch CUDA kernels Work with threads, blocks, grids, and execution hierarchies Manage data between the CPU and GPU Understand CUDA's different memory spaces Use synchronization and coordinate parallel work Design practical parallel algorithms Identify common CUDA programming mistakes Structure CUDA applications more effectively Build a solid foundation for further CUDA development and optimization The goal is not simply to memorize CUDA functions. Instead, you will develop a practical mental model of how CUDA programs execute and how GPU-oriented programming differs from conventional CPU programming. Whether you are a programmer new to GPU computing, a software developer expanding into parallel programming, or a technical professional looking to understand CUDA, this book provides a structured starting point for building useful GPU programming skills. Build the fundamentals first. Then use them to write better GPU programs.