Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Building Next-Generation GPU Software with CUDA 13.3 and C++26: A Comprehensive Guide to Parallel Algorithms, GPU Performance Engineering, Memory Opti

Building Next-Generation GPU Software with CUDA 13.3 and C++26: A Comprehensive Guide to Parallel Algorithms, GPU Performance Engineering, Memory Opti

Reeder, Ryan I.

Paperback

Series: Masterworks Technology, Book 5

Programming

ISBN13: 9798186082064
Publisher: Independently Published
Published: Jul 7 2026
Pages: 262
Weight: 1.35
Height: 0.55 Width: 8.50 Depth: 11.00
Language: English
Building Next-Generation GPU Software with CUDA 13.3 and C++26 is a comprehensive guide for developers, software engineers, researchers, and high-performance computing professionals who want to build efficient, scalable, and maintainable GPU-accelerated applications using modern programming techniques.

Beginning with the fundamentals of GPU architecture and parallel computing, this book establishes a solid foundation before progressing to advanced topics such as thread organization, memory hierarchies, kernel optimization, asynchronous execution, concurrency, performance profiling, multi-GPU programming, and enterprise-scale software design. Each chapter explains not only how modern GPU applications are developed, but also the engineering principles behind writing reliable, high-performance code.

The book also demonstrates how contemporary C++ language features can improve code quality, maintainability, and compile-time safety while supporting the demanding requirements of large-scale computational workloads. Readers will learn practical approaches for designing reusable software components, optimizing memory access, improving execution efficiency, and organizing complex projects for long-term development.

Real-world examples illustrate how GPU computing is applied across artificial intelligence, machine learning, scientific simulation, computer vision, numerical computing, data analytics, image processing, engineering, financial modeling, and other computationally intensive fields. Dedicated chapters cover performance engineering, debugging strategies, profiling techniques, cloud deployment considerations, and modern software architecture for production environments.

Inside this book, you will learn how to:

- Understand modern GPU architecture and parallel execution models.

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