clinfo - Print all known information about all available OpenCL platforms and devices in the system

  •        25

clinfo is a simple command-line application that enumerates all possible (known) properties of the OpenCL platform and devices available on the system. Inspired by AMD's program of the same name, it is coded in pure C and it tries to output all possible information, including those provided by platform-specific extensions, trying not to crash on unsupported properties (e.g. 1.2 properties on 1.1 platforms).

https://github.com/Oblomov/clinfo

Tags
Implementation
License
Platform

   




Related Projects

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.

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.

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.

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.

NyuziProcessor - GPGPU microprocessor architecture

  •    C++

Nyuzi is an experimental GPGPU processor hardware design focused on compute intensive tasks. It is optimized for use cases like blockchain mining, deep learning, and autonomous driving. This project includes a synthesizable hardware design written in System Verilog, an instruction set emulator, an LLVM based C/C++ compiler, software libraries, and tests. It can be used to experiment with microarchitectural and instruction set design tradeoffs.


Arraymancer - A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU, OpenCL and embedded devices

  •    Nim

Arraymancer is a tensor (N-dimensional array) project in Nim. The main focus is providing a fast and ergonomic CPU, Cuda and OpenCL ndarray library on which to build a scientific computing and in particular a deep learning ecosystem. The library is inspired by Numpy and PyTorch. The library provides ergonomics very similar to Numpy, Julia and Matlab but is fully parallel and significantly faster than those libraries. It is also faster than C-based Torch.

OpenCL

  •    

OpenCL is a general purpose programming language that provides an open standard to parallel device programming. The advantage of OpenCL is the hardware and software interoperability. This project focuses in the study and evaluation of OpenCL on graphic cards.

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.

emu - a language for programming GPUs, with a focus on ergonomics first and performance second

  •    Rust

⚠ Please note that while Emu 0.2.0 is quite usable, it suffers from 2 key issues. It firstly does nothing to minimize CPU-GPU data transfer and secondly it's compiler is not well-tested. These can be reasons not to use Emu 0.2.0. A new version of Emu is in the works, however, with significant improvements in the language, compiler, and compile-time checker. This new version of Emu should be released some time in Q4 of 2019. But unlike OpenCL/CUDA/Halide/Futhark, Emu is embedded in Rust. This lets it take advantage of the ecosystem in ways...

OSHI - Native Operating System and Hardware Information

  •    Java

OSHI is a free JNA-based (native) Operating System and Hardware Information library for Java. It does not require the installation of any additional native libraries and aims to provide a cross-platform implementation to retrieve system information, such as OS version, processes, memory & CPU usage, disks & partitions, devices, sensors, etc.

qcgpu-rust - A High Performance, Hardware accelerated, Quantum computer simulator in Rust

  •    Rust

The goal of QCGPU is to provide a library for the simulation of quantum computers that is fast, efficient and portable. QCGPU is written in Rust and uses OpenCL to run code on the CPU, GPU or any other OpenCL supported devices. This library is meant to be used both independently and alongside established tools for example compilers or more general and high level frameworks. If you are interested in using QCGPU with IBM's QISKit framework or QISKit ACQUA, please see the repository qiskit-addon-qcgpu.

RadeonProRender-Baikal

  •    C++

Baikal initiative has been started as a sample application demonstrating the usage of AMD® RadeonRays intersection engine, but evolved into a fully functional rendering engine aimed at graphics researchers, educational institutions and open-source enthusiasts in general. Baikal is fast and efficient GPU-based global illumination renderer implemented using OpenCL and relying on AMD® RadeonRays intersection engine. It is cross-platform and vendor independent. The only requirement it imposes on the hardware is OpenCL 1.2 support. Baikal maintains high level of performance across all vendors, but it is specifically optimized for AMD® GPUs and APUs.

RadeonRays_SDK - Radeon Rays is ray intersection acceleration library for hardware and software multiplatforms using CPU and GPU

  •    C++

Radeon Rays is ray intersection acceleration library provided by AMD which makes the most of the hardware and allows for efficient ray queries. Three backends support a range of use cases. App: Standalone sample/application featuring Radeon Rays OpenCL to implement a path tracer.

4-Centauri

  •    DotNet

GPGPUs offer significant horsepower in our computers that are unfortunately not easily available to .NET programs. <project name> is a system capable to map .NET bytecode into GPU IL (e.g. nVidia PTX) so that you can run .NET algorithms on state of the art hardware.

Hackintosh-Installer-University - open source tutorial & information collector for hackintosh installation

  •    Shell

📢 This is an open source tutorial & information collector for Hackintosh installations that does not charge readers any fee. 📢 We don't want to build a universal installation tutorial and, it's also impossible since every devices are different. We are here because we want to gather information and experiences, we want to build an index for most successful builds in github and make them be discovered more easily. When I was just a newbie, I didn't know how to get start building a hackintosh since I didn't know what's a bootloader and an EFI partition. It took me a really long time to find a helpful build in Github due to the deep location of that repo. So this is the purpose why we created this index.

OpenCL-caffe - This is a Experimental version of OpenCL by AMD Research, we now recommend you to use The official BVLC Caffe OpenCL branch is over at Caffe branch now at https://github

  •    C++

###OpenCL Caffe Experimental branch by AMD Reserach- No new development is happing on it. This is an OpenCL implementation of Caffe, a mainstream DNN framework (https://github.com/BVLC/caffe). It includes a largely complete Caffe feature set as of August 2015. The project is under active development to improve performance and add new features. Contributions from the community are welcome.

coriander - Build NVIDIA® CUDA™ code for OpenCL™ 1.2 devices

  •    LLVM

Build applications written in NVIDIA® CUDA™ code for OpenCL™ 1.2 devices. Other systems should work too, ideally. You will need at a minimum at least one OpenCL-enabled GPU, and appropriate OpenCL drivers installed, for the GPU. Both linux and Mac systems stand a reasonable chance of working ok.

collenchyma - Extendable HPC-Framework for CUDA, OpenCL and common CPU

  •    Rust

Collenchyma is an extensible, pluggable, backend-agnostic framework for parallel, high-performance computations on CUDA, OpenCL and common host CPU. It is fast, easy to build and provides an extensible Rust struct to execute operations on almost any machine, even if it does not have CUDA or OpenCL capable devices. Collenchyma's abstracts over the different computation languages (Native, OpenCL, Cuda) and let's you run highly-performant code, thanks to easy parallelization, on servers, desktops or mobiles without the need to adapt your code for the machine you deploy to. Collenchyma does not require OpenCL or Cuda on the machine and automatically falls back to the native host CPU, making your application highly flexible and fast to build.

futhark - :boom::computer::boom: A data-parallel functional programming language

  •    Haskell

Futhark is a purely functional data-parallel programming language. Its optimising compiler is able to compile it to typically very performant GPU code. The language and compiler is developed at DIKU at the University of Copenhagen, originally as part of the HIPERFIT centre. Although still under heavy development, Futhark is already useful for practical high-performance programming. For more information, see the website.

OpenVIDIA : Parallel GPU Computer Vision

  •    C

OpenVIDIA projects implement computer vision algorithms running on on graphics hardware such as single or multiple graphics processing units(GPUs) using OpenGL, Cg and CUDA-C. Some samples will soon support OpenCL and Direct Compute API's also.






We have large collection of open source products. Follow the tags from Tag Cloud >>


Open source products are scattered around the web. Please provide information about the open source projects you own / you use. Add Projects.