# Infatoshi/cuda-course

Repository: https://github.com/Infatoshi/cuda-course
Canonical: https://ross.abutalabs.com/products/cuda-course
Language: Cuda
License Family: other
Last push: 2026-03-11T05:55:03+00:00

## Health v2 (maintenance only)
Score: 55/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 71, release rhythm 35, longevity 56
- inputs: {"age_days": 786, "days_push": 175, "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 3972, forks 682 (observed 2026-08-28T04:08:30.841349+00:00)

## What it is
A free open-source CUDA programming course published with FreeCodeCamp, teaching GPU kernel development from C/C++ basics through optimized matrix multiplication, Triton, and PyTorch CUDA extensions. It culminates in building an MLP for MNIST in raw CUDA and targets NVIDIA GPUs on Ubuntu Linux.

## Use cases
- learn CUDA programming from scratch
- write and optimize GPU kernels for deep learning
- understand how llm.c-style projects work
- speed up matrix multiplication with CUDA
- write custom PyTorch CUDA extensions
- get started with Triton kernel development

## When to choose
- you have an NVIDIA GPU and want a structured, hands-on path into GPU programming
- you know Python and want to learn kernel optimization for ML workloads
- you want free course material with a concrete final project

## When to avoid
- you need AMD, Intel, or Apple GPU programming (course is NVIDIA/CUDA-specific)
- you want a production library rather than educational material
- you cannot access Linux, WSL, or Docker environments

## Facets
- artifact type: learning-resource
- maturity: active
- function: gpu-computing, machine-learning, developer-tools
- domain: gpu-computing, deep-learning, tutorials, education
- platform: python, cpp
- tags: cuda, triton, pytorch, kernel-optimization, free-code-camp, nvidia, linux, gpu

## Member repositories
- Infatoshi/cuda-course (main) score 55

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:30.841349+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 2026-08-29T18:24:21.100154+00:00, confidence not recorded.
  - readme: https://github.com/Infatoshi/cuda-course (fetched 2026-08-28T04:08:30.841349+00:00, sha 96fd62473708)
- Data as of 2026-08-30T08:39:29.467469+00:00.