GPGPU

To execute programs that use OpenCL, a compatible hardware runtime needs to be installed.

• opencl-mesa: free runtime for AMDGPU and Radeon
• opencl-amd^AUR: ROCr OpenCL and legacy OpenCL (a.k.a. orca) repackaged from AMD's ubuntu releases
• rocm-opencl-runtime^AUR: Part of AMD's ROCm GPU compute stack, officially supporting GFX8 and later cards (Fiji, Polaris, Vega), with unofficial and partial support for Navi10 based cards.
• amdapp-sdk^AUR: AMD CPU runtime

• opencl-nvidia: official NVIDIA runtime

• : a.k.a. the Neo OpenCL runtime, the open-source implementation for Intel HD Graphics GPU on Gen8 (Broadwell) and beyond.
• : the open-source implementation for Intel HD Graphics GPU on Gen7 (Ivy Bridge) and beyond, deprecated by Intel in favour of NEO OpenCL driver, remains recommended solution for legacy hardware platforms (e.g. Ivy Bridge, Haswell).
• : the proprietary implementation for Intel HD Graphics GPU on Gen7 (Ivy Bridge) and beyond, deprecated by Intel in favour of NEO OpenCL driver, remains recommended solution for legacy hardware platforms (e.g. Ivy Bridge, Haswell).
• : the implementation for Intel Core and Xeon processors. It also supports non-Intel CPUs.

• : LLVM-based OpenCL implementation (hardware independent)

The OpenCL ICD loader is supposed to be a platform-agnostic library that provides the means to load device-specific drivers through the OpenCL API. Most OpenCL vendors provide their own implementation of an OpenCL ICD loader, and these should all work with the other vendors' OpenCL implementations. Unfortunately, most vendors do not provide completely up-to-date ICD loaders, and therefore Arch Linux has decided to provide this library from a separate project (ocl-icd) which currently provides a functioning implementation of the current OpenCL API.

The other ICD loader libraries are installed as part of each vendor's SDK. If you want to ensure the ICD loader from the ocl-icd package is used, you can create a file in which adds /usr/lib to the dynamic program loader's search directories:

This is necessary because all the SDKs add their runtime's lib directories to the search path through files.

The available packages containing various OpenCL ICDs are:

• ocl-icd: recommended, most up-to-date
• by Intel. Provides OpenCL 2.0, deprecated in favour of .

For OpenCL development, the bare minimum additional packages required, are:

• ocl-icd: OpenCL ICD loader implementation, up to date with the latest OpenCL specification.
• : OpenCL C/C++ API headers.

The vendors' SDKs provide a multitude of tools and support libraries:

• : Intel OpenCL SDK (old version, new OpenCL SDKs are included in the INDE and Intel Media Server Studio)
• amdapp-sdk^AUR: This package is installed as and apart from SDK files it also contains a number of code samples (). It also provides the utility which lists OpenCL platforms and devices present in the system and displays detailed information about them. As the SDK itself contains a CPU OpenCL driver, no extra driver is needed to execute OpenCL on CPU devices (regardless of its vendor).
• : Nvidia's GPU SDK which includes support for OpenCL 1.1.

To see which OpenCL implementations are currently active on your system, use the following command:

$ ls /etc/OpenCL/vendors

To find out all possible (known) properties of the OpenCL platform and devices available on the system, install .

• JavaScript/HTML5: WebCL
• Python: python-pyopencl
• D: cl4d or DCompute
• Java: Aparapi or JOCL (a part of JogAmp)
• Mono/.NET: Open Toolkit
• Go: OpenCL bindings for Go
• Racket: Racket has a native interface on PLaneT that can be installed via raco.
• Rust: ocl
• Julia: OpenCL.jl

• Codeplay's proprietary implementation of SYCL 1.2.1. Can target SPIR, SPIR-V and experimentally PTX (NVIDIA) as device targets.
• : Open source implementation mainly driven by Xilinx.
• and : Free implementation built over AMD's HIP instead of OpenCL. Is able to run on AMD and NVIDIA GPUs.

Most SYCL implementations are able to compile the accelerator code to SPIR or SPIR-V. Both are intermediate languages designed by Khronos that can be consumed by an OpenCL driver. To check whether SPIR or SPIR-V are supported can be used:

ComputeCpp additionally ships with a tool that summarizes the relevant system information:

Drivers known to at least partially support SPIR or SPIR-V include , , and amdgpu-pro-opencl^AUR.

SYCL requires a working C++11 environment to be set up. There are a few open source libraries available:

• ComputeCpp SDK: Collection of code examples, integration for ComputeCpp
• SYCL-DNN: Neural network performance primitives
• SYCL-BLAS: Linear algebra performance primitives
• VisionCpp: Computer Vision library
• SYCL Parallel STL: GPU implementation of the C++17 parallel algorithms

The package installs all components in the directory . For compiling CUDA code, add to your include path in the compiler instructions. For example, this can be accomplished by adding to the compiler flags/options. To use , a gcc wrapper provided by NVIDIA, add to your path.

To find whether the installation was successful and whether CUDA is up and running, you can compile the CUDA samples. One way to check the installation is to run the sample.

• Fortran: PGI CUDA Fortran Compiler
• Haskell: The accelerate package lists available CUDA backends
• Java: JCuda
• Mathematica: CUDAlink
• Mono/.NET: CUDAfy.NET, managedCuda
• Perl: KappaCUDA, CUDA-Minimal
• Python:
• Ruby: rbcuda
• Rust: cuda-sys (bindings) or RustaCUDA (high-level wrapper)

The latest ROCm versions now includes OpenCL Image Support used by GPGPU accelerated software such as Darktable. ROCm with the AMDGPU open source graphics driver are all that is required. AMDGPU PRO is not required.