https://github.com/patrickroberts/gpcpu
Asynchronous Parallel Programming for TypedArray
https://github.com/patrickroberts/gpcpu
asynchronous-tasks javascript parallel-programming typedarray typescript web-workers worker-threads
Last synced: 3 months ago
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Asynchronous Parallel Programming for TypedArray
- Host: GitHub
- URL: https://github.com/patrickroberts/gpcpu
- Owner: patrickroberts
- License: mit
- Created: 2019-11-25T01:22:13.000Z (over 5 years ago)
- Default Branch: develop
- Last Pushed: 2023-01-05T01:40:58.000Z (over 2 years ago)
- Last Synced: 2024-04-28T20:04:23.705Z (about 1 year ago)
- Topics: asynchronous-tasks, javascript, parallel-programming, typedarray, typescript, web-workers, worker-threads
- Language: TypeScript
- Homepage: https://patrickroberts.github.io/gpcpu/
- Size: 651 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 12
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# gpcpu
Asynchronous Parallel Programming for TypedArray
## About
`gpcpu` enables user-friendly parallel programming in JavaScript by defining a `forEach()` function which executes a user-defined callback on multiple concurrent threads and returns a `Promise` that resolves when all the results have been copied to the TypedArray provided as input.
This significantly speeds up execution of sequential `for` loops over large typed arrays by delegating each block of execution to a concurrently running thread.
## Support
`gpcpu` provides out-of-the-box support for both browsers and [Node.js] by selectively using [Web Workers] or [Worker Threads] depending on the runtime environment. It also ships with typings for use in TypeScript projects.
## Install
### [npm] (Recommended)
```sh
npm i gpcpu
```
### [unpkg]
```html
```
## Usage
```js
import { Manager } from 'gpcpu';
// uses the number of threads your hardware can run concurrently by default
const parallel = new Manager();
const fltArr = new Float64Array(100000000);
console.time('parallel');
parallel.forEach(fltArr, (subArr, localIndex, globalIndex) => {
subArr[localIndex] = Math.sqrt(globalIndex);
}).then(() => {
// ~557ms on Intel Core i7-7700K @ 4.20GHz using 8 threads
console.timeEnd('parallel');
// use fltArr here
});
```
## Benchmark Comparison
```js
const fltArr = new Float64Array(100000000);
console.time('sequential');
for (let i = 0; i < fltArr.length; ++i) {
fltArr[i] = Math.sqrt(i);
}
// ~2564ms on Intel Core i7-7700K @ 4.20GHz
console.timeEnd('sequential');
// use fltArr here
```
## Documentation
Available on [Github Pages].
[Node.js]: https://nodejs.org
[Web Workers]: https://developer.mozilla.org/en-US/docs/Web/API/Web_Workers_API
[Worker Threads]: https://nodejs.org/api/worker_threads.html#worker_threads_worker_threads
[npm]: https://www.npmjs.com/package/gpcpu
[unpkg]: https://unpkg.com
[Github Pages]: https://patrickroberts.github.io/gpcpu/