How to compile OpenCL on Ubuntu?

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有刺的猬 2020-12-01 12:58

Question: What is needed headers and drivers are needed and where would I get them for compiling open CL on ubuntu using gcc/g++?


Info: for a while now I\'ve b

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  • 2020-12-01 13:47

    Things that worked for me in Ubuntu 16.04

    I have installed openCL on:

    SandyBridge CPU: cpu only

    IvyBridge GPU

    Nvidia GTX 950

    install packets

    Generic ubuntu packages for OpenCL

    Basic installation sudo apt install ocl-icd-libopencl1 sudo apt install opencl-headers sudo apt install clinfo

    Package that allows to compile OpenCL code (1.2 I think)

    Needed to link and compile sudo apt install ocl-icd-opencl-dev

    For Intel GT core

    Package that enables runnig openCL on Intel GT, IvyBridge and up

    sudo apt install beignet

    For SandyBridge Intel CPU and possible others

    Download this file OpenCL™ Runtime 16.1.1 for Intel® Core™ and Intel® Xeon® Processors for Ubuntu* (64-bit) On https://software.intel.com/en-us/articles/opencl-drivers#latest_linux_SDK_release

    Install packages for turning rpm to deb sudo apt-get install -y rpm alien libnuma1

    Untar downloaded file tar -xvf opencl_runtime_16.1.1_x64_ubuntu_6.4.0.25.tgz cd opencl_runtime_16.1.1_x64_ubuntu_6.4.0.25/rpm/ Turn rpm files to deb fakeroot alien --to-deb opencl-1.2-base-6.4.0.25-1.x86_64.rpm fakeroot alien --to-deb opencl-1.2-intel-cpu-6.4.0.25-1.x86_64.rpm Install .deb packages sudo dpkg -i opencl-1.2-base_6.4.0.25-2_amd64.deb sudo dpkg -i opencl-1.2-intel-cpu_6.4.0.25-2_amd64.deb Touch local config file sudo touch /etc/ld.so.conf.d/intelOpenCL.conf Open the file sudo vim /etc/ld.so.conf.d/intelOpenCL.conf and add the line

    /opt/intel/opencl-1.2-6.4.0.25/lib64/clinfo

    Create a vendors dir and add intel.icd sudo mkdir -p /etc/OpenCL/vendors sudo ln /opt/intel/opencl-1.2-6.4.0.25/etc/intel64.icd /etc/OpenCL/vendors/intel64.icd sudo ldconfig

    test if this worked

    clinfo should list your devices Dowload this file

    https://codeload.github.com/hpc12/tools/tar.gz/master

    Run this code to make sure everything works tar xzvf tools-master.tar.gz cd tools-master make ./print-devices ./cl-demo 1000 10 This should print out GOOD in the end

    For Nvidia

    install nvidia drivers (I used 370), this should include all the runtime dirvers

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  • 2020-12-01 13:58

    I've recently used similar process on a clean build on linux, setting up OpenCL with an NVIDIA card.

    Steps I took:

    1 - install the NVIDIA driver.

    2 - install the CUDA tool kit - (follwing the steps in the guide, there are many ways to do it, but I used the .deb installer, guide can be found here: http://docs.nvidia.com/cuda/cuda-getting-started-guide-for-linux/)

    3 - using apt-get install the OpenCL headers. Command: sudo apt-get install opencl-headers

    Using the : CL/opencl.h header I was able to compile C/C++ code using gcc/g++ and the flag: -lOpenCL

    Explaination of steps

    1 - Self explanatory

    2 - The CUDA toolkit also installs the OpenCL library (libOpencl.so) but not the header (at least not on my system)

    3 - hence the header can be installed with apt-get. The header files get stored in the /usr/include/CL directory

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  • 2020-12-01 14:00

    Ubuntu 20.04 with an NVIDIA Quadro M1200, Lenovo P51

    The software integration got a lot better since I had last tried, so I will do an update.

    First, at least for graphics, I needed to tweak some BIOS settings as mentioned at, not sure needed for OpenCL: https://askubuntu.com/questions/973605/ubuntu-17-10-boot-stuck-at-message-started-nvidia-persistence-daemon-after-ins/976578#976578

    Then, I find and install the latest driver available:

    apt-cache search nvidia-driver
    sudo apt install nvidia-driver-435 nvidia-opencl-dev
    

    You can also search under:

    software-properties-gtk
    

    in the "Additional Drivers" tab.

    Now I can compile and run the following test program:

    main.c

    #include <assert.h>
    #include <stdlib.h>
    #include <stdio.h>
    
    #define CL_TARGET_OPENCL_VERSION 220
    #define CL_USE_DEPRECATED_OPENCL_1_2_APIS
    #include <CL/cl.h>
    
    int main() {
        cl_command_queue command_queue;
        cl_context context;
        cl_device_id device;
        cl_int input = 1;
        cl_int kernel_result = 0;
        cl_kernel kernel;
        cl_mem buffer;
        cl_platform_id platform;
        cl_program program;
        const char *source = "__kernel void increment(int in, __global int* out) { out[0] = in + 1; }";
    
        clGetPlatformIDs(1, &platform, NULL);
        clGetDeviceIDs(platform, CL_DEVICE_TYPE_ALL, 1, &device, NULL);
        context = clCreateContext(NULL, 1, &device, NULL, NULL, NULL);
        command_queue = clCreateCommandQueue(context, device, 0, NULL);
        buffer = clCreateBuffer(context, CL_MEM_READ_WRITE | CL_MEM_ALLOC_HOST_PTR, sizeof(cl_int), NULL, NULL);
        program = clCreateProgramWithSource(context, 1, &source, NULL, NULL);
        clBuildProgram(program, 1, &device, "", NULL, NULL);
        kernel = clCreateKernel(program, "increment", NULL);
        clSetKernelArg(kernel, 0, sizeof(cl_int), &input);
        clSetKernelArg(kernel, 1, sizeof(cl_mem), &buffer);
        clEnqueueTask(command_queue, kernel, 0, NULL, NULL);
        clFlush(command_queue);
        clFinish(command_queue);
        clEnqueueReadBuffer(command_queue, buffer, CL_TRUE, 0, sizeof (cl_int), &kernel_result, 0, NULL, NULL);
    
        assert(kernel_result == 2);
        return EXIT_SUCCESS;
    }
    

    GitHub upstream

    with:

    gcc -ggdb3  -O0 -Wall -Wextra -pthread -std=c11 \
      -pedantic-errors -o main.out main.c -lm -pthread -lOpenCL
    ./main.out
    

    Notes:

    • find your GPU model: https://askubuntu.com/questions/72766/how-do-i-find-out-the-model-of-my-graphics-card
    • test that the driver is working: https://askubuntu.com/questions/68028/how-do-i-check-if-ubuntu-is-using-my-nvidia-graphics-card
    • similar answer for CUDA: https://askubuntu.com/questions/917356/how-to-verify-cuda-installation-in-16-04/1215237#1215237

    Ubuntu 15.10 with an NVIDIA NVS 5400M, Lenovo T430

    sudo apt-get install nvidia-352 nvidia-352-dev nvidia-prime nvidia-modprobe
    sudo ln -s /usr/include/nvidia-352/GL /usr/local/include
    sudo ln -s /usr/lib/x86_64-linux-gnu/libOpenCL.so.1 /usr/local/lib/libOpenCL.so
    

    Then use the header as:

    #include <CL/cl.h>
    

    And compile with:

    gcc -o main main.c -lOpenCL
    

    Notes:

    • do not install the nvidia-current package. It is old. Either apt-cache search nvidia and get the latest one, or use software-properties-gtk "Additional Drivers" tab.

    I really recommend upgrading to 15.10 to get this to work: I had never managed before.

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  • 2020-12-01 14:02

    To compile and run OpenCL code under Linux, you'll need four things:

    1) An NVIDIA Driver which supports OpenCL. The drivers packaged with Ubuntu are somewhat old, but they should still work just fine. Unless you have explicit need for current drivers, you should stick with the ones packaged with Ubuntu. To be clear, these are the same drivers installed through the restricted drivers manager. OpenCL libaries are shipped with driver, so to just run OpenCL programs driver should be enough.

    2) The CUDA toolkit. This includes the headers necessary to compile OpenCL code. Install this to the default location.

    3) The GPU Computing SDK (optional). This includes various NVIDIA specific support tools, as well as OpenCL code samples.

    All three of these items may be found at http://developer.nvidia.com/cuda-toolkit-40.

    4) OpenCL C++ bindings (optional). Strangely, they are not included with CUDA Toolkit, but in case you use C++, they could make your code much more redable. You can download them from http://www.khronos.org/registry/cl/api/1.1/cl.hpp, and just put it in /usr/local/cuda/include/CL an you desktop.

    Once these are installed, you'll need to perform a few more steps to be able to compile and run OpenCL outside of the NVIDIA SDK.

    1) The CUDA toolkit will have included the OpenCL headers (Listed at http://www.khronos.org/registry/cl/), likely they are in the directory /usr/local/cuda/include/CL. To make these headers available system wide, you should link this directory into /usr/include/, such that they may be accessed as /usr/include/CL/[headerfilename]. Instead of creating a symlink, you could add /usr/local/cuda/include to your C_INCLUDE_PATH and CPLUS_INCLUDE_PATH environment variables, but this would last for only currest session.

    2) Make sure that the OpenCL library (libOpenCL.so) is present in /usr/lib. This should have been put in place by the driver, so you shouldn't have to do anything.

    You're ready to write code. Make sure to include CL/cl.h (or CL/cl.hpp if you'd like to use C++ version of API) in any C(++) program which makes OpenCL API calls. When you compile, make sure to link against the OpenCL library (pass gcc the -lOpenCL flag).

    As far as your netbook, integrated graphics don't generally support OpenCL. In theory, AMD's APP Acceleration supports running OpenCL on the CPU, but it's not clear that it actually works.

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