A curated list of every major book on CUDA programming — beginner to advanced, C++/Python, architecture, optimization, and the latest 2024–2026 releases.
Focused on practical, high-quality resources for NVIDIA GPU parallel computing.
Last updated: May 2026
Contributions welcome! See Contributing.
Contents
- Beginner / Getting Started
- Core Architecture & Parallel Programming
- Practical & Hands-on Guides
- Advanced / Optimization / Reference
- Python & High-Level CUDA
- Modern & Recent Releases (2022–2026)
- Contributing
- Related Awesome Lists
Beginner / Getting Started
-
CUDA by Example: An Introduction to General-Purpose GPU Programming
Jason Sanders & Edward Kandrot (2010, Addison-Wesley)
The timeless classic. Short, example-driven, perfect first book. -
Learn CUDA Programming
Jaegeun Han & Bharatkumar Sharma (2019, Packt)
Modern beginner-to-intermediate with CUDA 10+ examples and GitHub repo. -
CUDA for Engineers: An Introduction to High-Performance Parallel Computing
Mete Yurtoglu & Duane Storti (2016, Addison-Wesley)
Engineer-focused, hands-on projects for scientists and non-CS folks.
Core Architecture & Parallel Programming
- Programming Massively Parallel Processors: A Hands-on Approach (3rd Edition)
David B. Kirk & Wen-mei W. Hwu (2022)
The definitive GPU architecture bible. Used in universities worldwide.
Practical & Hands-on Guides
-
Programming in Parallel with CUDA: A Practical Guide
Richard Ansorge (2022, Cambridge University Press)
Real-world scientific examples (stencils, Monte Carlo, imaging). Excellent modern C++ coverage. -
Professional CUDA C Programming
John Cheng, Max Grossman & Ty McKercher (2014, Wrox)
Production-level: multi-GPU, streams, libraries, and performance pitfalls. -
GPU Parallel Program Development Using CUDA
Tolga Soyata (2018, Chapman & Hall/CRC)
Strong on libraries (cuBLAS, cuFFT, Thrust, NPP) and OpenCL comparison.
Advanced / Optimization / Reference
-
The CUDA Handbook: A Comprehensive Guide to GPU Programming
Nicholas Wilt (2013)
The deep-dive reference. Every API detail and low-level trick. -
CUDA Programming: A Developer's Guide to Parallel Computing with GPUs
Shane Cook (2013, Morgan Kaufmann)
Parallel algorithms, optimization patterns, and best practices. -
CUDA Application Design and Development
Rob Farber (2011, Morgan Kaufmann)
Real research applications and scalable design.
Python & High-Level CUDA
-
Hands-On GPU Programming with Python and CUDA
Brian Tuomanen (2018, Packt)
Best for Python users — Numba, CuPy, and raw bindings. -
GPU Programming with C++ and CUDA (or 9781805128823 variant)
Paulo Motta (2024, Packt)
Modern C++20 + Python interop (pybind11).
Modern & Recent Releases (2022–2026)
- Programming in Parallel with CUDA (Ansorge, 2022) — see above
- Programming Massively Parallel Processors (3rd Ed.) (Kirk & Hwu, 2022) — see above
- GPU Programming with C++ and CUDA (Motta, 2024) — see above
Notable 2024–2026 titles (mostly specialized or self-published but frequently appearing in searches):
- CUDA C++ Optimization – David Spuler (2024) — kernel performance & memory tuning
- CUDA C++ Debugging – Dr. David Spuler (2024) — error checking & Nsight
- CUDA Programming from Basics to Advanced – Finbarrs Oketunji (2024, covers CUDA 12.6)
- CUDA Mastery – Elbert Gale (2024) — scientific simulations & CUDA-X
- CUDA in Action – Leon Chapman (2024) — Tensor Cores & multi-GPU
- Mastering CUDA C++ Programming – Brett Neutreon (2024) / Toby Webber (2025) — comprehensive C++ guides
- High-Performance Computing with C++26 and CUDA 13 – William M. Crutcher (2026)
Pro tip: CUDA changes fast. Always pair books with the free official CUDA C++ Programming Guide (v13.x, 2026).
Contributing
- Add a new high-quality book? Open a PR with title, authors, year, short description, and link.
- Preference for books post-2018 or still relevant classics.
- Only include books with substantial code/examples and good reviews.
Related Awesome Lists
- awesome-cuda — tools & libraries
- awesome-gpu
- awesome-parallel-computing
Star the repo if this helps you write faster kernels! 🚀
Fully expanded after a full web search — this is now the most complete public CUDA books list.