GitHub - alternbits/awesome-cuda-books: A curated list of best cuda programming books · GitHub
/" data-turbo-transient="true" />
Skip to content
Search or jump to...
Search code, repositories, users, issues, pull requests...
-->
Search
Clear
Search syntax tips
Provide feedback
--><br>We read every piece of feedback, and take your input very seriously.
Include my email address so I can be contacted
Cancel
Submit feedback
Saved searches
Use saved searches to filter your results more quickly
-->
Name
Query
To see all available qualifiers, see our documentation.
Cancel
Create saved search
Sign in
/;ref_cta:Sign up;ref_loc:header logged out"}"<br>Sign up
Appearance settings
Resetting focus
You signed in with another tab or window. Reload to refresh your session.<br>You signed out in another tab or window. Reload to refresh your session.<br>You switched accounts on another tab or window. Reload to refresh your session.
Dismiss alert
{{ message }}
alternbits
awesome-cuda-books
Public
Notifications<br>You must be signed in to change notification settings
Fork
Star<br>22
main
BranchesTags
Go to file
CodeOpen more actions menu
Folders and files<br>NameNameLast commit message<br>Last commit date<br>Latest commit
History<br>1 Commit<br>1 Commit
readme.md
readme.md
View all files
Repository files navigation
Awesome CUDA Books
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...