js - turbo.js - perform massive parallel computations in your browser with GPGPU.

  •        94

turbo.js is a small library that makes it easier to perform complex calculations that can be done in parallel. The actual calculation performed (the kernel executed) uses the GPU for execution. This enables you to work on an array of values all at once. turbo.js is compatible with all browsers (even IE when not using ES6 template strings) and most desktop and mobile GPUs.




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This repo contains a selection of projects designed to help you learn the basics of computer graphics. We'll be writing shaders to render interactive two-dimensional and three-dimensional scenes. This workshop covers fragment shaders (GLSL), procedural texture generation, rasterization, lighting calculations, and real-time ray tracing.

Vc - SIMD Vector Classes for C++

  •    C++

Recent generations of CPUs, and GPUs in particular, require data-parallel codes for full efficiency. Data parallelism requires that the same sequence of operations is applied to different input data. CPUs and GPUs can thus reduce the necessary hardware for instruction decoding and scheduling in favor of more arithmetic and logic units, which execute the same instructions synchronously. On CPU architectures this is implemented via SIMD registers and instructions. A single SIMD register can store N values and a single SIMD instruction can execute N operations on those values. On GPU architectures N threads run in perfect sync, fed by a single instruction decoder/scheduler. Each thread has local memory and a given index to calculate the offsets in memory for loads and stores. Current C++ compilers can do automatic transformation of scalar codes to SIMD instructions (auto-vectorization). However, the compiler must reconstruct an intrinsic property of the algorithm that was lost when the developer wrote a purely scalar implementation in C++. Consequently, C++ compilers cannot vectorize any given code to its most efficient data-parallel variant. Especially larger data-parallel loops, spanning over multiple functions or even translation units, will often not be transformed into efficient SIMD code.

glsl-optimizer - GLSL optimizer based on Mesa's GLSL compiler

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A C++ library that takes GLSL shaders, does some GPU-independent optimizations on them and outputs GLSL or Metal source back. Optimizations are function inlining, dead code removal, copy propagation, constant folding, constant propagation, arithmetic optimizations and so on. Apparently quite a few mobile platforms are pretty bad at optimizing shaders; and unfortunately they also lack offline shader compilers. So using a GLSL optimizer offline before can make the shader run much faster on a platform like that. See performance numbers in this blog post.

WebMonkeys - Massively parallel GPU programming on JavaScript, simple and clean.

  •    Javascript

Allows you to spawn thousands of parallel tasks on the GPU with the simplest, dumbest API possible. It works on the browser (with browserify) and on Node.js. It is ES5-compatible and doesn't require any WebGL extension. set/get allow you to send/receive data from the GPU, and work creates a number of parallel tasks (monkeys) that can read, process and rewrite that data. The language used is GLSL 1.0, extended array access (foo(index), usable anywhere on the source), setters (foo(index) := value, usable on the end only), and int i, a global variable with the index of the monkey.

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GPU accelerated handwritten digit recognition with regl. Note that this network will probably be slower than the corresponding network implemented on the CPU. This is because of the overhead associated with transferring data to and from the GPU. But in the future we will attempt implementing more complex networks in the browser, such as Neural Style, and then we think that we will see a significant speedup compared to the CPU.

glslEditor - Simple WebGL Fragment Shader Editor

  •    Javascript

Friendly GLSL Shader editor based on Codemirror compatible with glslViewer (C++/OpenGL ES) and glslCanvas (JS/WebGL). Was originaly develop to work as a embebed editor for The Book of Shaders. But now have grown as a stand alone Web app. Thanks to their compatibility with other apps of this ecosystems like glslViewer that runs in the RaspberryPi directly from console, GlslEditor interact with other projects like OpenFrame.io allowing the user to export the shaders to frames with only one button.

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HTML GL solves "the slow DOM problem" by creating WebGL representations of DOM elements and hiding actual DOM after. This speeds up HTML/CSS animations and transformations by using 3D hardware acceleration and allows to apply OpenGL effects as modern 3D games have. Using HTML GL you still work with HTML/CSS as you are common to, but DOM elements are just facades to their WebGL representations. These GPU accelerated textures are very effective from resources consuming perspective and are very cheap to transform or animate.

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Easy, powerful, portable, absurdly fast numerical calculations. Includes static dispatch with inlining based on your platform and vector types, zero-allocation iteration, vectorized loading/storing, and support for uneven collections. The vector size is entirely determined by the machine you’re compiling for - it attempts to use the largest vector size supported by your machine, and works on any platform or architecture (see below for details).

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  •    Javascript

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  •    C++

I start this addon while I was working on Efecto Mariposa. Is the result of adapting different well know algorithms to GLSL Shaders for openFrameworks. An important feature of ofxFX is it ability for fast-prototyping mixing different classes using the << operator.

awesome-webgl - A curated list of awesome WebGL libraries, resources and much more


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  •    Javascript

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  •    Javascript

Alternatively, you can pack the extension yourself and load by dropping the .crx file in the Extensions page.

phenomenon - ⚡️ A fast 2kB low-level WebGL API.

  •    Javascript

Phenomenon is a very small, low-level WebGL library that provides the essentials to deliver a high performance experience. Its core functionality is built around the idea of moving millions of particles around using the power of the GPU. Returns an instance of Phenomenon.

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