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.
lwjgl kotlin opengl opencl openal vulkan bindings glfw vr opengl-es jvmThe following code snippet demonstrates the general workflow of nnvm compiler.Licensed under an Apache-2.0 license.
computation-graph deep-learning optimization deployment nnvm tvm cuda opencl rocm metalMACE 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.
deep-learning neural-network opencl neon hvx machine-learningLicense & Contributions: The software is provided under MIT license. Contributions to this project are accepted under the same license.
neon opencl computer-vision arm armv7 armv8 aarch64 machine-learning simd android cpp neural-networkBoost.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.
opencl boost c-plus-plus cpp compute gpu gpgpu performance hpchashcat 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.
hashcat password cracking gpgpu opencl hashesThis 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.
library performance deep-neural-networks deep-learning cpp opencl x64 x86-64 openmp avx2 amx sse41 tbb aarch64 avx512 bfloat16 oneapi onednn dpcpp xe-architectureSilk.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+.
audio opengl native graphics vulkan opencl glfw game-development openal scientific-visualization silk graphics-library haptics hacktoberfest 3dVkFFT 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.
hpc vulkan opencl cuda convolution fft hip dct r2c r2r vulkan-fft c2rApache 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.
machine-learning performance deep-learning metal compiler gpu vulkan opencl tensor spirv rocmNeanderthal 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.
clojure-library matrix gpu gpu-computing gpgpu opencl cuda high-performance-computing vectorization api matrix-factorization matrix-multiplication matrix-functions matrix-calculationsVexCL 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.
opencl cuda c-plus-plus gpgpu scientific-computing cpp11OpenCL 1.2 implementation for Tensorflow
opencl tensorflow gpu mac radeon intel nvidia ubuntuChlorine 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.
cplusplus opencl compute gpgpuThis is editor of OpenCL files (*.cl). Editor supports syntax highlighting, autocomplete, check of errors and warnings, debugging.
cl opencl.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.
binding openclBrahma 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.
cpu gpu multicore opencl
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