Search Results for "gpu" - Page 8
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Showing 229 open source projects for "gpu"
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PixelFlow
A Processing/Java library for high performance GPU-Computing (GLSL)
PixelFlow is a Processing library focused on advanced graphics and visual effects, offering an extensive suite of GPU-based tools for visual artists, researchers, and creative coders. It enables real-time simulation and rendering of complex effects such as fluid dynamics, reaction-diffusion systems, soft shadows, and more, all powered by GLSL shaders. Its modular structure allows for chaining and composing various visual effects easily, making it ideal for installations, performances, and visual experimentation. -
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PyTorch Book
PyTorch tutorials and fun projects including neural talk
...The current version of the code is based on pytorch 1.0.1, if you want to use an older version please git checkout v0.4or git checkout v0.3. Legacy code has better python2/python3 compatibility, CPU/GPU compatibility test. The new version of the code has not been fully tested, it has been tested under GPU and python3. But in theory there shouldn't be too many problems on python2 and CPU. The basic part (the first five chapters) explains the content of PyTorch. This part introduces the main modules in PyTorch and some tools commonly used in deep learning. ... -
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Caffe Framework
Caffe, a fast open framework for deep learning
...Caffe is released under the BSD 2-Clause license. Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine then deploy to commodity clusters or mobile devices. Extensible code fosters active development. In Caffe’s first year, it has been forked by over 1,000 developers and had many significant changes contributed back. Thanks to these contributors the framework tracks the state-of-the-art in both code and models. -
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Edward
A probabilistic programming language in TensorFlow
...Edward fuses three fields, Bayesian statistics and machine learning, deep learning, and probabilistic programming. Edward is built on TensorFlow. It enables features such as computational graphs, distributed training, CPU/GPU integration, automatic differentiation, and visualization with TensorBoard. Expectation-Maximization, pseudo-marginal and ABC methods, and message passing algorithms. -
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Intel neon
Intel® Nervana™ reference deep learning framework
...We want to highlight that neon v2.0.0+ has been optimized for much better performance on CPUs by enabling Intel Math Kernel Library (MKL). The DNN (Deep Neural Networks) component of MKL that is used by neon is provided free of charge and downloaded automatically as part of the neon installation. The gpu backend is selected by default, so the above command is equivalent to if a compatible GPU resource is found on the system. The Intel Math Kernel Library takes advantages of the parallelization and vectorization capabilities of Intel Xeon and Xeon Phi systems. When hyperthreading is enabled on the system, we recommend the following KMP_AFFINITY setting to make sure parallel threads are 1:1 mapped to the available physical cores. -
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Starling Filters
A collection of filters for use with the Starling AS3 framework
Starling-Filters is an open-source collection of filter effects for the Starling AS3 framework. These filters allow developers using Starling (a GPU accelerated 2D rendering framework in Flash/AIR) to apply image processing / visual effects (e.g. blur, glow, etc.) in their Starling-based applications. The repo has versions for Starling 2.0 (on master) and older filters archived for Starling 1.x. A collection of filters for use with the Starling AS3 framework. The master branch contains filters for use with Starling 2.0. -
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Caffe2
Caffe2 is a lightweight, modular, and scalable deep learning framework
Caffe2 is a lightweight, modular, and scalable deep learning framework. Building on the original Caffe, Caffe2 is designed with expression, speed, and modularity in mind. Caffe2 is a deep learning framework that provides an easy and straightforward way for you to experiment with deep learning and leverage community contributions of new models and algorithms. You can bring your creations to scale using the power of GPUs in the cloud or to the masses on mobile with Caffe2’s cross-platform... -
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SoAx
Structure of Arrays of multiple types
Structures of arrays (SoA) are generally faster than arrays of structures (AoS) while AoS are more handy. This project (SoAx) combines the advantages of both. By means of C++(11) meta-template programming SoAx achieves maximal performance (efficient use of vector units and cache of modern CPUs) while providing a very convenient user interface (including object-oriented element handling) and flexibility. It has been designed to handle list-like sets of particles (similar to struct {int id;... -
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Starling Extension Graphics
flash.display.Graphics style extension for the Starling Flash GPU
Starling-Extension-Graphics is an extension for the Starling framework (which itself is a GPU-accelerated 2D framework for Flash/AIR via Stage3D). This extension adds graphics primitives (fills, strokes, planes etc.) that mimic flash.display.Graphics-style drawing but implemented in a GPU-friendly manner. It automatically triangulates vector shapes, letting developers use familiar drawing APIs but get performance benefits of GPU rendering via Starling. -
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Caffe
A fast open framework for deep learning
...It’s got an expressive architecture that encourages application and innovation, and extensible code that’s great for active development. Caffe also offers great speed, capable of processing over 60M images per day with a single NVIDIA K40 GPU. It’s arguably one of the fastest convnet implementations around. Caffe is developed by the Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and a great community of contributors that continue to make Caffe state-of-the-art in both code and models. It’s been used in numerous projects, from startup prototypes and academic research projects, to large scale industrial applications. -
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Starling Extension Particle System
A particle system for the Starling framework
The Starling Extension Particle System is an ActionScript extension for the Starling framework that enables developers to integrate particle effects created with the "Particle Designer" tool by 71squared into Starling-based applications. The demo-directory contains a sample project. To compile it, add a reference to the Starling library and add the source directory that contains the particle system classes. The project contains 4 sample configurations. Switch between configurations in... -
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GXUI
An experimental Go cross platform UI library
GXUI is an experimental, cross-platform GUI toolkit for Go that explored what a modern, GPU-accelerated desktop UI could look like for the language. It provided a set of widgets, layout containers, and event models that ran on Windows, macOS, and Linux, targeting a single Go API surface. Rendering was driven by a graphics backend so that animations, text, and compositing could be smooth without relying on heavyweight native bindings. -
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ND2D
A Flash Molehill (Stage3D) GPU accelerated 2D game engine
ND2D is a 2D game framework for Flash that uses Stage3D / Molehill (i.e. the GPU acceleration in newer Flash Player versions). It allows game developers to build 2D games with lots of sprites, leveraging GPU for better performance. It includes display tree constructs, sprite sheets, particle systems, cameras, post-processing etc., made to simplify building high-performance 2D content in Flash. ND2D was built to make an ease use of hardware accelerated 2D content in the Flashplayer. ... -
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HTML GL
Get as many FPS as you need and amazing effects by rendering HTML/CSS
...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. Include HTMLGL.js into the project. Elements will be rendered in WebGL and their CSS Transform properties will be mapped to WebGL representation transformations. So DOM node itself will not be animated or displayed in order to avoid resource consumption. -
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WebGL Heatmap
A high performance WebGL/JS heatmap display library
webgl-heatmap is a browser-side rendering library that uses the GPU via WebGL to draw smooth, continuous heatmaps from large numbers of data points. Instead of relying on CPU-bound canvas operations, it leverages fragment shaders and additive blending to accumulate intensity and colorize results in real time. The API lets you push points or weighted samples into a buffer and then renders a gradient map where hot areas emerge organically from density rather than discrete markers. ... -
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GPUImage
iOS framework for GPU-based image and video processing
The GPUImage framework is a BSD-licensed iOS library that lets you apply GPU-accelerated filters and other effects to images, live camera video, and movies. In comparison to Core Image (part of iOS 5.0), GPUImage allows you to write your own custom filters, supports deployment to iOS 4.0, and has a slightly simpler interface. However, it currently lacks some of the more advanced features of Core Image, such as facial detection. -
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GTkNN
GPU-based Textual kNN (GT-kNN)
The following code is a parallel kNN implementation that uses GPUs for the high dimensional data in text classification. You can use it to classify documents using kNN or to generate meta-features based on the distances between a query document and its k nearest neigbors -
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qemu
My changes to qemu for legacy free GPU passthrough
My changes to qemu for legacy free GPU passthrough. Only one adapter can use legacy vga regions at same time. This is an attemp to achieve a qemu gpu passthrough without legacy vga accesses to graphics card. Legacy io accesses to vga registers are replaced through MMIO accesses. Legacy accesses to vga memory are replaced through accesses to plain framebuffer. This avoids vga arbiter problems in linux kernel. -
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MXLib is a C++ wrapper around the Intel® Integrated Performance Primitives (IPP) library and NVidia NPP CUDA library. You can use either IPP code (or a subset of functions that do not require IPP) on the CPU side, or use NPP/CUDA on the GPU side, or use both together. The function syntax is similar to that found in MatLab and the library is designed to make it easy to port your code from MatLab to C++. The idea is to provide Scientists, Engineers, Researchers and other non full-time programmers an easy to use, high performance library of functions.
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Genetic Programming in OpenCL is a parallel implementation of genetic programming targeted at heterogeneous devices, such as CPU and GPU. It is written in OpenCL, an open standard for portable parallel programming across many computing platforms.
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jQuery Transit
Super-smooth CSS3 transformations and transitions for jQuery
jQuery Transit is a classic jQuery plugin that brought ergonomic, chainable CSS3 transitions and transforms to web apps before modern animation APIs were commonplace. It exposes a simple .transition() method so you can animate transforms, opacity, colors, and other CSS properties with minimal code. Under the hood, it leans on GPU-accelerated CSS transforms where available, falling back gracefully, which made complex motion feel smooth even on modest devices. The plugin abstracts away vendor prefixes and browser quirks from an era with inconsistent CSS3 support, letting teams focus on intent instead of compatibility. It integrates with the jQuery queue system, so transitions can be sequenced or synchronized with other effects without race conditions. ... -
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MicroLua DS
MicroLua brings Lua on the Nintendo DS for easy programming
MicroLua brings the programming language Lua on the Nintendo DS for easy and fast development of beautiful homebrews! Based on brunni's µLibrary, µLua is a Lua interpreter featuring fast drawings and many important functionalities. You can exploit your Nintendo DS with the simplistic yet powerful Lua language! On your cartridge, MicroLua is a NDS executable that shows as its frontend a great graphical shell from which you can explore your cartridge and run Lua scripts written for... -
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HIPAcc
Heterogeneous Image Processing Acceleration (HIPACC) Framework
HIPAcc development has moved to github: https://github.com/hipacc HIPAcc allows to design image processing kernels and algorithms in a domain-specific language (DSL). From this high-level description, low-level target code for GPU accelerators is generated using source-to-source translation. As back ends, the framework supports CUDA, OpenCL, and Renderscript. HIPAcc allows programmers to develop imaging applications while providing high productivity, flexibility and portability as well as competitive performance: the same algorithm description serves as basis for targeting different GPU accelerators and low-level languages. -
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Java/C Comparative Benchmarks
Java and C Comparative Performance Benchmarks
...There are benchmarks for bit twiddling, numerical computing, data structure manipulation, concurrent computing, callouts to native libraries, and, graphics processing units (GPU) utilization. -
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StarlingPunk
StarlingPunk is a framework built on top the Starling library
StarlingPunk is a game framework built on top of the Starling GPU-accelerated 2D library (AS3 / Flash / AIR). It is inspired by FlashPunk: it gives structure (entities, worlds), collision detection systems, tile maps, etc., and is intended to help developers organize 2D game code more cleanly while benefiting from Starling’s performance. It has features for quick prototyping and reusing code between projects.
