# PacktPublishing/Learn-CUDA-Programming

Learn CUDA Programming, published by Packt

Repository: https://github.com/PacktPublishing/Learn-CUDA-Programming
Canonical: https://ross.abutalabs.com/products/learn-cuda-programming
Language: Cuda
License: MIT
License Family: permissive
Last push: 2023-12-30T08:15:53+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": 2976, "days_push": 977, "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 1261, forks 260 (observed 2026-08-28T04:04:10.098018+00:00)

## What it is
The companion code repository for the Packt book 'Learn CUDA Programming', a beginner's guide to GPU programming and parallel computing with CUDA 10.x and C/C++. It contains chapter-by-chapter example code covering GPU operations, performance optimization, profiling, multi-GPU scaling, and deep learning acceleration.

## Use cases
- learn CUDA GPU programming from scratch
- study parallel computing examples in C/C++
- optimize GPU application performance
- profile and debug CUDA applications
- scale workloads across multiple GPUs and nodes
- accelerate deep learning models with GPUs
- practice GPU programming with Python interop and OpenACC

## When to choose
- you are following the Packt book and want runnable code for each chapter
- you are a C/C++ programmer new to GPU and parallel computing
- you want hands-on examples of CUDA profiling, optimization, and multi-GPU scaling
- you are a deep learning practitioner wanting GPU performance insights

## When to avoid
- you need a production CUDA library or framework rather than educational code
- you want a maintained, actively updated CUDA tutorial (code targets CUDA 10.x)
- you have no C/C++ background and need a gentler introduction
- you need CUDA examples for recent GPU architectures or newer CUDA versions

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: gpu-computing, machine-learning, developer-tools
- domain: gpu-computing, tutorials, machine-learning, developer-tools
- platform: cpp, python, windows
- tags: cuda, book-code, packt, parallel-computing, high-performance-computing, gpu-programming, openacc, profiling, gpu, linux, macos

## Member repositories
- PacktPublishing/Learn-CUDA-Programming (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:10.098018+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 2026-08-30T05:04:16.886275+00:00, confidence not recorded.
  - readme: https://github.com/PacktPublishing/Learn-CUDA-Programming (fetched 2026-08-28T04:04:10.098018+00:00, sha a803e082ef7a)
- Data as of 2026-08-30T08:39:29.467469+00:00.