Displaying 1 to 20 from 82 results

lwjgl3 - LWJGL is a Java library that enables cross-platform access to popular native APIs useful in the development of graphics (OpenGL), audio (OpenAL) and parallel computing (OpenCL) applications

  •    Kotlin

LWJGL (https://www.lwjgl.org) is a Java library that enables cross-platform access to popular native APIs useful in the development of graphics (OpenGL/Vulkan), audio (OpenAL) and parallel computing (OpenCL) applications. This access is direct and high-performance, yet also wrapped in a type-safe and user-friendly layer, appropriate for the Java ecosystem.LWJGL is an enabling technology and provides low-level access. It is not a framework and does not provide higher-level utilities than what the native libraries expose. As such, novice programmers are encouraged to try one of the frameworks or game engines that make use of LWJGL, before working directly with the library.

nnvm - Bring deep learning to bare metal

  •    C++

The following code snippet demonstrates the general workflow of nnvm compiler.Licensed under an Apache-2.0 license.

mace - MACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms

  •    C++

MACE Model Zoo contains several common neural networks and models which will be built daily against a list of mobile phones. The benchmark results can be found in the CI result page (choose the latest passed pipeline, click release step and you will see the benchmark results). Any kind of contribution is welcome. For bug reports, feature requests, please just open an issue without any hesitation. For code contributions, it's strongly suggested to open an issue for discussion first. For more details, please refer to the contribution guide.

compute - A C++ GPU Computing Library for OpenCL

  •    C++

Boost.Compute is a GPU/parallel-computing library for C++ based on OpenCL. The core library is a thin C++ wrapper over the OpenCL API and provides access to compute devices, contexts, command queues and memory buffers.

hashcat - World's fastest and most advanced password recovery utility

  •    C

hashcat is the world's fastest and most advanced password recovery utility, supporting five unique modes of attack for over 200 highly-optimized hashing algorithms. hashcat currently supports CPUs, GPUs, and other hardware accelerators on Linux, Windows, and macOS, and has facilities to help enable distributed password cracking. hashcat is licensed under the MIT license. Refer to docs/license.txt for more information.

oneDNN - oneAPI Deep Neural Network Library (oneDNN)

  •    C++

This software was previously known as Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN) and Deep Neural Network Library (DNNL). oneDNN is intended for deep learning applications and framework developers interested in improving application performance on Intel CPUs and GPUs. Deep learning practitioners should use one of the applications enabled with oneDNN.


  •    CSharp

Silk.NET is your one-stop-shop for high-speed .NET multimedia, graphics, and compute; providing bindings to popular low-level APIs such as OpenGL, OpenCL, OpenAL, OpenXR, GLFW, SDL, Vulkan, Assimp, and DirectX. Silk.NET works on any .NET Standard 2.0 compliant platform, including .NET 5.0, Xamarin, .NET Framework 4.6.1+, and .NET Core 2.0+.

VkFFT - Vulkan/CUDA/HIP/OpenCL Fast Fourier Transform library

  •    C++

VkFFT is an efficient GPU-accelerated multidimensional Fast Fourier Transform library for Vulkan/CUDA/HIP/OpenCL projects. VkFFT aims to provide the community with an open-source alternative to Nvidia's cuFFT library while achieving better performance. VkFFT is written in C language and supports Vulkan, CUDA, HIP and OpenCL as backends. Vulkan version: Include the vkFFT.h file and glslang compiler. Provide the library with correctly chosen VKFFT_BACKEND definition (VKFFT_BACKEND=0 for Vulkan). Sample CMakeLists.txt file configures project based on Vulkan_FFT.cpp file, which contains examples on how to use VkFFT to perform FFT, iFFT and convolution calculations, use zero padding, multiple feature/batch convolutions, C2C FFTs of big systems, R2C/C2R transforms, R2R DCT-II, III and IV, double precision FFTs, half precision FFTs. For single and double precision, Vulkan 1.0 is required. For half precision, Vulkan 1.1 is required.

TVM - Open deep learning compiler stack for cpu, gpu and specialized accelerators

  •    Python

Apache TVM, a deep learning compiler that enables access to high-performance machine learning anywhere for everyone. TVM’s diverse community of hardware vendors, compiler engineers and ML researchers work together to build a unified, programmable software stack, that enriches the entire ML technology ecosystem and make it accessible to the wider ML community. TVM empowers users to leverage community-driven ML-based optimizations to push the limits and amplify the reach of their research and development, which in turn raises the collective performance of all ML, while driving its costs down.

neanderthal - Fast Clojure Matrix Library

  •    Clojure

Neanderthal is a Clojure library for fast matrix and linear algebra computations based on the highly optimized native libraries of BLAS and LAPACK computation routines for both CPU and GPU.. Read the documentation at Neanderthal Web Site.

vexcl - VexCL is a C++ vector expression template library for OpenCL/CUDA

  •    C++

VexCL is a vector expression template library for OpenCL/CUDA. It has been created for ease of GPGPU development with C++. VexCL strives to reduce amount of boilerplate code needed to develop GPGPU applications. The library provides convenient and intuitive notation for vector arithmetic, reduction, sparse matrix-vector products, etc. Multi-device and even multi-platform computations are supported. The source code of the library is distributed under very permissive MIT license.

Chlorine - Dead Simple OpenCL

  •    C++

Chlorine is the easiest way to interact with OpenCL compatible devices. It is a header-only C++11 library that allows you to write cross-platform code that runs on GPUs without ever touching the complicated OpenCL API, leaving you free to write code that matters: kernels that process data. Chlorine is composed of just two headers: chlorine.hpp, and its dependency, the OpenCL C++ Bindings. To integrate Chlorine into your own project, install OpenCL; then add chlorine/include to your include paths and link with OpenCL. Chlorine also requires a compiler with C++11 support. An example of how to use Chlorine is below, or read a more detailed walkthrough if you prefer.


  •    DotNet

Luminal is a simple object oriented .NET wrapper for OpenCL. It is developed in C#, using P/Invoke calls in the background.

CLEditor - OpenCL editor


This is editor of OpenCL files (*.cl). Editor supports syntax highlighting, autocomplete, check of errors and warnings, debugging.


  •    DotNet

.NET bindings for OpenCL that are easy-to-use and true to the original API. There is no OOP abstraction, nor will there ever be. OpenCL.Net is meant to be small, fast (with as little explicit marshaling as possible) and .NET friendly at the same time.


  •    DotNet

Luminoise is an OpenCL accelerated coherent noise library for .NET. It uses Luminal for access to OpenCL (hence, "Luminoise"), and is modeled after LibNoise.


  •    DotNet

Brahma is a library for C#, to provide high-level access to parallel streaming computations on a variety of processors. Brahma uses C#'s LINQ syntax to write kernels that are compiled dynamically. All the glue/kernel code required is *automatically* generated by by Brahma.

cl - OpenCL binding for Erlang

  •    C

OpenCL binding for Erlang

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