Table of contents
GPU.JS
Single-file JavaScript library for GPU acceleration.
As GPU.JS is an open source project, you can find more
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Performance Boost
GPU.JS leverages the power of the GPU to perform computations, potentially offering significant performance improvements over CPU-based computations, especially for parallelizable tasks.
JavaScript Integration
GPU.JS is built for JavaScript environments, allowing easy integration into existing JavaScript projects without the need for external languages or complex setups.
Ease of Use
The library provides a high-level API that abstracts much of the complexity associated with writing GPU code, making it more accessible to developers who might not be familiar with GPU programming.
Cross-Platform
GPU.JS runs in the browser and on Node.js, allowing developers to write platform-independent code that can execute on both client and server environments.
Real-Time Processing
By utilizing GPU acceleration, GPU.JS can handle real-time data processing tasks efficiently, which is beneficial for applications such as simulations, data visualizations, and animations.
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Check the traffic stats of GPU.JS on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of GPU.JS on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of GPU.JS's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of GPU.JS on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
The latest comments about GPU.JS on Reddit. This can help you find out how popualr the product is and what people think about it.
Imho there are js libraries which goes through the traditional rendering based shader path to emulate general purpose computations on the GPU, gpu.js for example https://gpu.rocks/#/. - Source: Hacker News / 4 months ago
How will this compare to Gpu.js? https://gpu.rocks/. - Source: Hacker News / over 2 years ago
Https://gpu.rocks/#/ Sorry, this is barely gameplay related, just interested if that could be kept synced. - Source: Hacker News / about 3 years ago
You can refresh the page to get a different random generator function. This code uses the great gpu.js library (https://gpu.rocks) to speed things up. The basic idea is to generate colors for each pixel at each given time step by running a randomly-generated function. The function is influenced by the concept of neural nets as universal function approximators. Basically, it takes the pixel x/y coordinates and some... - Source: Hacker News / almost 4 years ago
Website nowadays have high end graphics and requires a lot of processing power so it might be a good IDEA to utilize the power of GPU. It might sound complicated but its really simple actually. Because there are many library out there to help you out. For example GPU.js. It also switch backs to regular mode if the user device don't have a GPU so no worries there. So get started now by reading the DOCS. - Source: dev.to / almost 4 years ago
I know there's a lot of Javascript developers on this forum. If you want to get into GPU programming, I highly recommend gpu.js [1] library as a jumping off point. It's amazing how powerful computers are and how we squander most our cycles. [1] https://gpu.rocks/#/ Disclaimer: I have one un-merged PR in the gpu.js repo. - Source: Hacker News / almost 4 years ago
One of the clear advantages of a native CSS engine over its JavaScript equivalent, is that itโs written in a low level language such as C or C++. That can be compensated with the usage of Web Assembly, where we can write our code with Rust and compile it to a low-level language that can run on the browser. To top things up, we can use WebGL or a library such as GPU.JS to run vector calculations in parallel using... - Source: dev.to / about 4 years ago
Https://gpu.rocks/#/ - This library transpiles JS into GLSL so you don't even need to know GLSL at all. I started with this for a few months and eventually started to edit the raw GLSL output it was producing to do further optimisations. Source: over 4 years ago
Because CSS animations can take advantage of GPU acceleration. When you use properties like translateZ, translate3d, max-width, min-width, etc in your animations, CSS will shift the painting of those animations from the CPU over to the GPU. This is something that is not really possible in JS (unless you use something like GPU.js, but a whole dependency just for some silly animations? kek). Source: over 4 years ago
The way Desmos works is it compiles your Desmos code to JavaScript by converting, e.g. a*b^4*sin(x) to a*Math.pow(b,4)*sin(x). It converts this string to a function, then calls the function when it needs to. Converting this JavaScript code in turn to C-like code for a GPU would be difficult to get working for all the functions Desmos produces. https://gpu.rocks/#/ provides GPU support for some Javascript, but it... Source: over 4 years ago
That seems like pushing javascript too far, but you might try https://gpu.rocks/. It's a bare bones matrix library with gpu acceleration, that might be the bump you need. Source: over 4 years ago
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