A curated list of every major book on CUDA programming — beginner to advanced, C++/Python, architecture, optimization, and the latest 2024–2026 releases.
Last updated: May 2026
- 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
-
CUDA by Example: An Introduction to General-Purpose GPU Programming
-
CUDA for Engineers: An Introduction to High-Performance Parallel Computing
-
GPU Programming with C++ and CUDA (or 9781805128823 variant)
- 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).
- 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.
- awesome-cuda — tools & libraries
- awesome-gpu
- awesome-parallel-computing
Star the repo if this helps you write faster kernels! 🚀