![]() Some try to measure the frame rate over time or use a combination of other features, but none of them are very robust. ![]() There’s no good way to feature-detect powerful devices. Unfortunately, some browsers will gladly say that they support WebGL, but they are simply too weak to run the code with good performance. In fact, our javascript heavy React and WebGL website even renders without Javascript support: □ We also want to make sure text content is available even if WebGL isn’t supported. It’s fast, has a good ecosystem of plugins to speed up common tasks, and offers server-side rendering out of the box.Īs any fan of static websites knows, server-side rendering is great for SEO and accessibility since the content can be accessed without executing a bunch of Javascript. We usually use Gatsby.js on our projects. Visitors have short attention spans, and it can impact conversion rates and sales. Not all websites can afford a long loading animation. ![]() However, for many projects, having quick access to the content, a high level of accessibility and SEO are equally important to delivering a memorable creative experience. If you’re doing a cool campaign site or interactive experience, many of these assumptions might be correct. Sometimes, text content is rendered only as WebGL textures, which makes the content essentially images. Some websites even lock the user out if the browser lacks support for a modern feature.īecause of these assumptions, it’s common to create and position all content using Javascript (e.g. For this reason, it’s common for WebGL apps to preload and pre-render textures before showing the website.Įverybody loves to scroll - Having only one long page means the WebGL canvas can create all objects for the whole website on page load (during the preloader animation), and there are no requests to load new pages or new assets to worry about.Įverybody has a modern browser - Building for advanced browsers and adding polyfills for missing features. Large images are known to cause lag as they are uploaded to the GPU for the first time. Contributions are welcome via the Propel GitHub project.Everybody loves a cool loading animation - Having a preloader allows the browser to download all assets before showing the website. Propel is early in its development lifecycle and has not yet reached a stable release. To use Propel within your Node.js or browser-based application source code, import the relevent modules from Propel using ES modules, e.g.: import from "propel" In browsers, include the optimized JavaScript package: To see examples in Node.js, run the following from the command line: npm install -g ts-node In Node.js, run the following from the command-line: npm install propel Installation of Propel is straightforward. Propel is authored in TypeScript, and usage of ts-node is encouraged as it gives a TypeScript execution environment and REPL for Node.js. The project provides an introductory neural network example. The browser version of Propel is intended more for demonstration purposes or more straightforward calculations.įor machine learning usage, developers are encouraged to create machine learning models server-side and then quickly deploy them as web-based demos. The Node.js version uses TensorFlow's C API and supports the targeting of multiple GPUs and TCP connections. Propel works in the browser with WebGL and deeplearn.js. Rather than starting from scratch, Propel leverages other foundational technologies. Propel runs in multiple environments, but for performance reasons, usage of Node.js is encouraged for computationally intensive computing. Per the Propel project creator and original Node.js founder Ryan Dahl, "JavaScript is a fast, dynamic language which, we think, could act as an ideal workflow for scientific programmers of all sorts."ĭahl is not alone in this perspective, as many other projects are attempting to improve computational computing and machine learning in JavaScript including brain.js, ConvNetJS, deeplearn.js, math.js, mljs, Natural, Synaptic, and Webdnn. Propel provides an approach similar to NumPy. Propel strives to eliminate any computational computing gap between Python and JavaScript. While Python is often the default language of choice for machine learning, JavaScript usage is growing in popularity. Propel is a new JavaScript scientific computing library leveraging GPU hardware for computations to support machine learning and other scientific computing in JavaScript.
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