# NVIDIA-developer-blog/code-samples

Source code examples from the Parallel Forall Blog

Repository: https://github.com/NVIDIA-developer-blog/code-samples
Canonical: https://ross.abutalabs.com/products/code-samples
Language: HTML
License: BSD-3-Clause
License Family: permissive
Last push: 2025-09-23T21:26:24+00:00

## Health v2 (maintenance only)
Score: 52/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 43, release rhythm 35, longevity 100
- inputs: {"age_days": 5287, "days_push": 344, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1331, forks 641 (observed 2026-08-28T04:04:24.313759+00:00)

## What it is
A collection of source code examples accompanying articles from NVIDIA's Parallel Forall developer blog, covering CUDA, OpenACC, Python, and MATLAB. It serves as reference material for learning GPU and parallel programming techniques.

## Use cases
- learn CUDA programming with working examples
- find sample code for OpenACC directives
- study GPU acceleration techniques from blog posts
- get reference implementations for parallel computing tutorials
- explore NVIDIA developer blog code samples

## When to choose
- you are following a Parallel Forall blog post and want its accompanying code
- you want hands-on examples for learning CUDA or OpenACC
- you need reference snippets for GPU programming in C++ or Python

## When to avoid
- you need a production-ready library or framework
- you want a structured course rather than loosely organized samples
- you need non-NVIDIA GPU computing examples

## Facets
- artifact type: learning-resource
- maturity: active
- function: developer-tools
- domain: gpu-computing, tutorials, developer-tools
- platform: cpp, python, cross-platform
- tags: cuda, openacc, code-samples, nvidia, parallel-computing, examples, gpu

## Member repositories
- NVIDIA-developer-blog/code-samples (main) score 52

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:24.313759+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 2026-08-30T04:45:14.713152+00:00, confidence not recorded.
  - readme: https://github.com/NVIDIA-developer-blog/code-samples (fetched 2026-08-28T04:04:24.313759+00:00, sha 1c78f6683015)
- Data as of 2026-08-30T08:39:29.467469+00:00.