# amandaghassaei/gpu-io

A GPU-accelerated computing library for running physics simulations and other GPGPU computations in a web browser.

Repository: https://github.com/amandaghassaei/gpu-io
Canonical: https://ross.abutalabs.com/products/gpu-io
Homepage: https://apps.amandaghassaei.com/gpu-io/examples/
Language: TypeScript
License: MIT
License Family: permissive
Topics: glsl, gpgpu, gpu, webgl, canvas, shaders, physics, threejs, shader, particles, parallel, simulation, webgl1, webgl2
Last push: 2024-01-31T23:07:13+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2129, "days_push": 945, "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 1482, forks 58 (observed 2026-08-28T04:04:51.052634+00:00)

## What it is
gpu-io is a TypeScript WebGL library for composing GPU-accelerated computing workflows in the browser. It handles WebGL state management, shader caching, and cross-browser compatibility so developers can run physics simulations, particle systems, and general GPGPU computations with minimal boilerplate.

## Use cases
- run real-time fluid simulations in the browser
- simulate reaction-diffusion patterns on the GPU
- build particle or agent-based simulations like Physarum networks
- implement cellular automata like Conway's Game of Life
- do GPU-accelerated image processing in WebGL
- solve the wave equation and render results with Three.js
- run general purpose GPU computations without writing raw WebGL boilerplate

## When to choose
- you need GPU-parallel simulations or computations running in a web browser
- you want WebGL1/WebGL2 fallbacks and cross-browser polyfills handled for you
- you want to pass GPU computation results directly to Three.js without reading back to CPU
- you need to render simulation output directly to a WebGL canvas with interactivity

## When to avoid
- you need WebGPU features today (support is only planned)
- you are doing general-purpose GPU computing outside the browser
- you need a full physics engine with rigid bodies and collisions rather than shader-based simulation
- your project requires long-term maintenance guarantees given the small single-maintainer project

## Facets
- artifact type: library
- maturity: active
- function: simulation, graphics, image-processing, gpu-computing
- domain: simulation, graphics, web-development
- platform: browser, cross-platform
- tags: webgl, gpgpu, glsl, shaders, physics-simulation, particles, threejs, cellular-automata, fluid-simulation, game-development, web-server

## Member repositories
- amandaghassaei/gpu-io (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:51.052634+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 2026-08-30T04:34:05.756020+00:00, confidence not recorded.
  - readme: https://github.com/amandaghassaei/gpu-io (fetched 2026-08-28T04:04:51.052634+00:00, sha b2066dff3094)
  - homepage: https://apps.amandaghassaei.com/gpu-io/examples/ (fetched 2026-08-29T11:40:56.068320+00:00, sha 0811faab8b16)
  - registry_npm: https://registry.npmjs.org/gpu-io (fetched 2026-08-29T11:40:56.077554+00:00, sha 6d1fd1e7bb46)
- Data as of 2026-08-30T08:39:29.467469+00:00.