GitHub - alternbits/awesome-cuda-books: A curated list of best cuda programming books
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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.