# cinight/MinimalCompute

Repository: https://github.com/cinight/MinimalCompute
Canonical: https://ross.abutalabs.com/products/minimalcompute
Language: C#
License Family: other
Topics: unity3d, compute-shaders, unity
Last push: 2026-03-24T21:44:47+00:00

## Health v2 (maintenance only)
Score: 65/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 73, release rhythm 35, longevity 100
- inputs: {"age_days": 2522, "days_push": 162, "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 1522, forks 145 (observed 2026-08-28T04:04:58.009932+00:00)

## What it is
A collection of minimal Unity example scenes demonstrating compute shaders, compute buffers, and CPU-GPU data transport. It includes both Built-in RP and URP scenes covering textures, structured buffers, GPU particles, fluids, and async GPU readback.

## Use cases
- learn unity compute shaders
- examples of cpu to gpu data transfer in unity
- gpu fluid simulation example
- gpu particles with compute buffers
- async gpu readback example
- structured buffer usage in unity shaders

## When to choose
- you are learning Unity compute shaders from small runnable scenes
- you need reference implementations for compute buffers, AsyncGPUReadback, or GPU fluids in Unity 6

## When to avoid
- you need a production-ready library or framework to drop into a project
- you target platforms other than Windows DX11 without testing
- you need a licensed, packaged asset with support

## Facets
- artifact type: learning-resource
- maturity: active
- function: graphics, simulation, developer-tools
- domain: graphics, simulation, tutorials
- platform: windows, game-engine, cross-platform
- tags: unity, compute-shaders, gpu, example-scenes, urp, gpgpu, game-development

## Member repositories
- cinight/MinimalCompute (main) score 65

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:58.009932+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 2026-08-30T04:31:46.559456+00:00, confidence not recorded.
  - readme: https://github.com/cinight/MinimalCompute (fetched 2026-08-28T04:04:58.009932+00:00, sha 82b217e9fe71)
- Data as of 2026-08-30T08:39:29.467469+00:00.