1. Programming Massively Parallel Processors: A Hands-on Approach
Written by a team of experts including Wen-mei W. Hwu, David B. Kirk, and Izzat El Hajj, this book serves as an essential guide for anyone looking to master the nuances of parallel computing. It offers a hands-on approach to understanding the architecture behind massively parallel processors and teaches you how to effectively program them. The book is packed with real-world examples that help reinforce your understanding of complex concepts. At a price of $78.70, it’s a worthwhile investment for programmers eager to dive deep into GPU programming.
2. CUDA by Example: An Introduction to General-Purpose GPU Programming
This book by Jason Sanders and Edward Kandrot is a must-read for anyone looking to get started with GPU programming. “CUDA by Example” presents the fundamentals of CUDA programming through clear examples and simple explanations, making it accessible for beginners. The authors emphasize practical knowledge, letting readers learn through hands-on coding. Priced at $47.49, this introductory book is a steal for those wanting to kickstart their journey into parallel programming.
3. Professional CUDA C Programming
If you’re serious about taking your skills to a professional level, then John Cheng’s “Professional CUDA C Programming” is for you. This book is designed for those who have some familiarity with CUDA and want to dig deeper into advanced concepts. It covers essential programming techniques and best practices to create high-performance applications. With a price tag of $28.56, it’s an invaluable resource for aspiring CUDA developers.
4. CUDA C++ Optimization: Coding Faster GPU Kernels
David Spuler takes optimization to the next level with his book “CUDA C++ Optimization: Coding Faster GPU Kernels”. This text is targeted at more experienced programmers, focusing on enhancing the performance of CUDA applications through optimization techniques. If you’re looking to improve your coding speed and efficiency, then this is a must-read at an affordable price of $14.95.
5. Programming in Parallel with CUDA: A Practical Guide
Richard Ansorge’s “Programming in Parallel with CUDA” is a comprehensive guide that combines practical advice and programming techniques. It addresses common challenges faced by developers and provides valuable insights into programming paradigms. The engaging writing style and clear explanations make this book a great choice for those wanting to strengthen their parallel programming skills, all for $62.79.
6. Multicore and GPU Programming: An Integrated Approach
Gerassimos Barlas delivers a holistic approach to programming in his book, “Multicore and GPU Programming: An Integrated Approach”. This resource emphasizes the integration of multicore systems with GPU programming, making it a unique addition to your library. By learning to harness the full potential of hardware, developers can create robust applications. Available for $73.32, it’s essential for programmers looking to expand their knowledge base.
7. Hands-On GPU Programming with Python and CUDA
For those who prefer Python, Dr. Brian Tuomanen’s “Hands-On GPU Programming with Python and CUDA” is the perfect match. This book simplifies complex programming concepts by using a popular language to teach GPU programming. It’s user-friendly and perfect for those just starting out, all for a reasonable price of $45.97.
8. CUDA for Engineers: An Introduction to High-Performance Parallel Computing
“CUDA for Engineers” by Duane Storti and Mete Yurtoglu is designed for engineering students and professionals who want to gain insight into high-performance computing using CUDA. The book is rich with examples tailored for engineering applications, making the concepts easier to comprehend. This high-quality book is available for $44.99.
9. CUDA Fortran for Scientists and Engineers: Best Practices for Efficient CUDA Fortran Programming
This comprehensive text by Gregory Ruetsch and Massimiliano Fatica focuses on CUDA Fortran, offering best practices that cater specifically to scientists and engineers. By highlighting the efficient use of CUDA Fortran, this book is vital for professionals looking to maximize computational efficiency. Priced at $129.95, it stands as a premium resource in the field.
10. CUDA C++ Debugging: Safer GPU Kernel Programming
David Spuler once again brings his expertise with “CUDA C++ Debugging: Safer GPU Kernel Programming”. This book is focused on the crucial aspect of debugging in GPU programming, providing you with robust methodologies and techniques to ensure your GPU kernels operate correctly. At a price of $14.95, it’s a great addition to any serious programmer’s library.
