# brucefan1983/CUDA-Programming

Sample codes for my CUDA programming book

Repository: https://github.com/brucefan1983/CUDA-Programming
Canonical: https://ross.abutalabs.com/products/cuda-programming
Language: Cuda
License: GPL-3.0
License Family: copyleft
Topics: cuda-programming, gpu-programming, molecular-dynamics-simulation
Last push: 2025-12-14T13:27:03+00:00

## Health v2 (maintenance only)
Score: 48/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 57, release rhythm 8, longevity 100
- inputs: {"age_days": 2679, "days_push": 262, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2091, forks 388 (observed 2026-08-28T04:06:12.482917+00:00)

## What it is
Sample source code accompanying a Chinese CUDA programming book (with an English version in progress) by Bruce Fan. It provides runnable CUDA C++ examples covering thread organization, memory, speedup techniques, and molecular dynamics simulation on GPUs.

## Use cases
- learn CUDA programming from scratch
- find example CUDA kernel code
- understand GPU thread organization
- learn unified memory in CUDA
- GPU-accelerate molecular dynamics simulations
- study CUDA performance optimization techniques

## When to avoid
- you need production-ready CUDA libraries
- you want Python-first CUDA tutorials (the pyCUDA companion repo is unmaintained)
- you need coverage of advanced topics like multi-GPU or NCCL

## Facets
- artifact type: learning-resource
- maturity: active
- function: gpu-computing, simulation, developer-tools
- domain: gpu-computing, tutorials, simulation
- platform: cpp, windows
- tags: cuda, nvidia, gpu-programming, book-samples, molecular-dynamics, c-plus-plus, gpu, linux, macos

## Member repositories
- brucefan1983/CUDA-Programming (main) score 48

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:12.482917+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:55:32.404853+00:00, confidence not recorded.
  - readme: https://github.com/brucefan1983/CUDA-Programming (fetched 2026-08-28T04:06:12.482917+00:00, sha 44a7a338bad9)
- Data as of 2026-08-30T08:39:29.467469+00:00.