Package Exports

detect-gpu

This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (detect-gpu) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

Readme

Detect GPU

Classify GPU's based on their benchmark score in order to provide an adaptive experience.

Demo

Live demo

Installation

By default we use the UNPKG CDN to host the benchmark data. If you would like to serve the benchmark data yourself download the required benchmarking data from benchmarks.tar.gz and serve it from a public directory.

Make sure you have Node.js installed.

 $ npm install detect-gpu

Usage

import { getGPUTier } from 'detect-gpu';

(async () => {
  const gpuTier = await getGPUTier({
    benchmarksURL?: string; // (Default, "https://unpkg.com/detect-gpu@${PKG_VERSION}/dist/benchmarks") Provide location of where to access benchmark data
    failIfMajorPerformanceCaveat?: boolean; // (Default, false) Fail to detect if the WebGL implementation determines the performance would be dramatically lower than the equivalent OpenGL
    glContext?: WebGLRenderingContext | WebGL2RenderingContext; // (Default, undefined) Optionally pass in a WebGL context to avoid creating a temporary one internally
    desktopTiers?: number[]; // (Default, [0, 15, 30, 60]) Framerate per tier
    mobileTiers?: number[]; // (Default, [0, 15, 30, 60]) Framerate per tier
    override?: { // (Default, false) Override specific functionality, useful for development
      renderer?: string; // Manually override reported GPU renderer string
      isIpad?: boolean; // Manually report device as being an iPad
      isMobile?: boolean; // Manually report device as being a mobile device
      screenSize?: { width: number; height: number }; // Manually adjust reported screenSize
      loadBenchmarks?: (file: string) => Promise<TModelEntry[] | undefined>; // Optionally modify method for loading benchmark data
    };
  })

  // Example output:
  // {
  //   "tier": 1,
  //   "isMobile": false,
  //   "type": "BENCHMARK",
  //   "fps": 21,
  //   "gpu": "intel iris graphics 6100"
  // }
})();

detect-gpu uses rendering benchmark scores (framerate, normalized by resolution) in order to determine what tier should be assigned to the user's GPU. If no WebGLContext can be created, the GPU is blocklisted or the GPU has reported to render on less than 15 fps tier: 0 is assigned. One should provide a fallback to a non-WebGL experience.

Based on the reported fps the GPU is then classified into either tier: 1 (> 15 fps), tier: 2 (> 30 fps) or tier: 3 (> 60 fps). The higher the tier the more graphically intensive workload you can offer to the user.

Changelog

Licence

My work is released under the MIT license.

detect-gpu uses both mobile and desktop benchmarking scores from https://gfxbench.com.