# Tony-Tan/CUDA_Freshman

Repository: https://github.com/Tony-Tan/CUDA_Freshman
Canonical: https://ross.abutalabs.com/products/cuda_freshman
Language: Cuda
License Family: other
Last push: 2024-01-16T06:14:23+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3145, "days_push": 960, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2792, forks 514 (observed 2026-08-28T04:07:22.217027+00:00)

## What it is
A collection of CUDA example programs accompanying a Chinese-language blog tutorial series on GPU programming, partly based on the book 'Professional CUDA C Programming'. It covers the CUDA programming model, execution model, memory hierarchy, and streams with runnable code for each lesson.

## Use cases
- learn CUDA programming from scratch
- understand GPU thread and warp execution
- study CUDA shared memory and global memory optimization
- learn CUDA streams and concurrent kernel execution
- find example code for CUDA memory management
- practice parallel reduction and loop unrolling on GPU

## When to choose
- you are a beginner learning CUDA with accompanying blog explanations
- you want runnable examples of core CUDA concepts like memory, warps, and streams
- you prefer tutorial-style code over reference documentation

## When to avoid
- you need production-ready CUDA libraries or frameworks
- you want an English-language tutorial (content is mostly in Chinese)
- you need maintained, licensed code for commercial use (no license is provided)

## Facets
- artifact type: learning-resource
- maturity: stable
- function: gpu-computing, developer-tools, benchmarking
- domain: gpu-computing, tutorials, developer-tools
- platform: cpp, cross-platform
- tags: cuda, gpu-programming, tutorial-code, parallel-computing, c-plus-plus, gpu, linux

## Member repositories
- Tony-Tan/CUDA_Freshman (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:22.217027+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 2026-08-30T08:15:14.717373+00:00, confidence not recorded.
  - readme: https://github.com/Tony-Tan/CUDA_Freshman (fetched 2026-08-28T04:07:22.217027+00:00, sha c79581f6a5c2)
- Data as of 2026-08-30T08:39:29.467469+00:00.