Ubuntu 20.04 LTS安装openclliyangzmx的专栏-

CPU: AMD® Ryzen threadripper 3970x 32-core processor × 64 

内存: 220.1 GiB

图形: AMD® Radeon rx 580 2048sp

DiskCapacity: 3.8 TB

OS Name: Ubuntu 20.04 LTS

系统信息:

 nickli@Earth:/opt/work$ lsb_release -a No LSB modules are available. Distributor ID: Ubuntu Description: Ubuntu 20.04 LTS Release: 20.04 Codename: focal nickli@Earth:/opt/work$ cat /proc/version Linux version 5.4.0-37-generic (buildd@lcy01-amd64-001) (gcc version 9.3.0 (Ubuntu 9.3.0-10ubuntu2)) #41-Ubuntu SMP Wed Jun 3 18:57:02 UTC 2020 

本人所用显卡驱动的下载链接:

https://drivers.amd.com/drivers/linux/amdgpu-pro-20.20-1089974-ubuntu-20.04.tar.xz

请您根据您实际的情况下载对应的驱动

然后安装驱动:

 $ mkdir amd-gpu $ cd amd-gpu/ $ tar xvf /download/amdgpu-pro-20.20-1089974-ubuntu-20.04.tar.xz $ cd amdgpu-pro-20.20-1089974-ubuntu-20.04/ $ sudo ./amdgpu-install

安装完成后需要重启电脑(祝您好运~)

然后安装clinfo工具查看显卡对OpenCL的支持情况:

 $ sudo apt-get install clinfo $ cliinfo nickli@Earth:/opt/work$ clinfo  Number of platforms                               1   Platform Name                                   AMD Accelerated Parallel Processing   Platform Vendor                                 Advanced Micro Devices, Inc.   Platform Version                                OpenCL 2.1 AMD-APP (3110.6)   Platform Profile                                FULL_PROFILE   Platform Extensions                             cl_khr_icd cl_amd_event_callback cl_amd_offline_devices    Platform Host timer resolution                  1ns   Platform Extensions function suffix             AMD    Platform Name                                   AMD Accelerated Parallel Processing Number of devices                                 1   Device Name                                     Ellesmere   Device Vendor                                   Advanced Micro Devices, Inc.   Device Vendor ID                                0x1002   Device Version                                  OpenCL 1.2 AMD-APP (3110.6)   Driver Version                                  3110.6   Device OpenCL C Version                         OpenCL C 1.2  ... ...

安装OpenCL的头文件和库:

 nickli@Earth:/opt/work$ sudo apt-get install opencl-headers Reading package lists... Done Building dependency tree        Reading state information... Done The following packages were automatically installed and are no longer required:   guile-2.0-libs libgsoap-2.8.91 libm17n-0 libotf0 libqt5opengl5 libvncserver1 m17n-db virtualbox-dkms ... ... Setting up opencl-clhpp-headers (2.1.0~~git51-gc5063c3-1) ... Setting up opencl-c-headers (2.2~2019.08.06-g0d5f18c-1) ... Setting up opencl-headers (2.2~2019.08.06-g0d5f18c-1) ...  nickli@Earth:/opt/work$ sudo apt install opencl-dev [sudo] password for liyang:  Reading package lists... Done Building dependency tree        Reading state information... Done Note, selecting 'ocl-icd-opencl-dev' instead of 'opencl-dev' The following packages were automatically installed and are no longer required:   guile-2.0-libs libgsoap-2.8.91 libm17n-0 libotf0 libqt5opengl5 libvncserver1 m17n-db virtualbox-dkms ... ... Unpacking ocl-icd-opencl-dev:amd64 (2.2.11-1ubuntu1) ... Setting up ocl-icd-opencl-dev:amd64 (2.2.11-1ubuntu1) ... 

假设:

源码路径:/opt/work/cl/

主机源码文件名: cl.c, 同级别目录编写CMakeLists.txt文件:

 cmake_minimum_required( VERSION 2.8.10 )  project( Example )  find_package( OpenCL REQUIRED )  include_directories( ${OPENCL_INCLUDE_DIR} )  add_executable( example cl.c )  target_link_libraries( example ${OPENCL_LIBRARIES} )

执行cmake命令生成Makefile(/opt/work/cl/下):

 $ mkdir build $ cd build $ cmake -DOPENCL_INCLUDE_DIR=/usr/include -DOPENCL_LIBRARIES=/lib/x86_64-linux-gnu/libOpenCL.so ..

然后编写cl.c源程序:

 #define PROGRAM_FILE "matvec.cl" #define KERNEL_FUNC "matvec_mult"  #include <stdio.h> #include <stdlib.h> #include <string.h> #include <sys/types.h>  #ifdef MAC #include <OpenCL/cl.h> #else #include <CL/cl.h> #endif  void show_float4(float data[4]) {     int i = 0;      for(i = 0; i < 4; i++) {         if(i != 3) {             printf("%f, ", data[i]);         } else {             printf("%f", data[i]);         }     }     printf("nn"); }  int main() {     cl_platform_id platform;     cl_device_id device;     cl_context context;     cl_command_queue queue;     cl_int i, err;      cl_program program;     FILE *program_handle;     char *program_buffer, *program_log;     size_t program_size, log_size;     cl_kernel kernel;     size_t work_units_per_kernel;      float mat[16], vec[4], result[4];     float correct[4] = {0.0f, 0.0f, 0.0f, 0.0f};     cl_mem mat_buff, vec_buff, res_buff;      for(i = 0; i < 16; i++) {         mat[i] = i * 2.0f;     }      for(i = 0; i < 4; i++) {         vec[i] = i * 3.0f;         correct[0] += mat[i]        * vec[i];         correct[1] += mat[i + 4]    * vec[i];         correct[2] += mat[i + 8]    * vec[i];         correct[3] += mat[i + 12]   * vec[i];     }     clGetPlatformIDs(1, &platform, NULL);     clGetDeviceIDs(platform, CL_DEVICE_TYPE_GPU, 1, &device, NULL);     context = clCreateContext(NULL, 1, &device, NULL, NULL, &err);     program_handle = fopen(PROGRAM_FILE, "r");     fseek(program_handle, 0, SEEK_END);     program_size = ftell(program_handle);     rewind(program_handle);     program_buffer = (char *)malloc(program_size + 1);     program_buffer[program_size] = '';     fread(program_buffer, sizeof(char), program_size, program_handle);     fclose(program_handle);      program = clCreateProgramWithSource(context, 1, (const char **)&program_buffer, &program_size, &err);     free(program_buffer);      clGetProgramInfo(program, CL_PROGRAM_SOURCE, 0, NULL, &program_size);     program_buffer = (char *)malloc(program_size);     clGetProgramInfo(program, CL_PROGRAM_SOURCE, program_size, program_buffer, 0);     printf("Program Source: n%snn", program_buffer);     free(program_buffer);      err = clBuildProgram(program, 0, NULL, NULL, NULL, NULL);     if(err < 0) {         printf("CL_PROGRAM_BUILD_STATUS: %dn", err);         clGetProgramBuildInfo(program, device, CL_PROGRAM_BUILD_LOG, 0, NULL, &log_size);         printf("log_size: %ldn", log_size);         program_log = (char *) malloc (log_size + 1);         program_log[log_size] = '';         clGetProgramBuildInfo(program, device, CL_PROGRAM_BUILD_LOG, log_size, program_log, NULL);         printf("Program log: %sn", program_log);         free(program_log);         exit(1);     }      kernel = clCreateKernel(program, KERNEL_FUNC, &err);     if(0 > err) {         printf("clCreateKernel status: %dn", (int32_t)err);         exit(1);     }     queue = clCreateCommandQueue(context, device, 0, &err);     if(0 > err) {         printf("clCreateCommandQueue status: %dn", (int32_t)err);         exit(1);     }     mat_buff = clCreateBuffer(context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, sizeof(float) * 16, mat, &err);     vec_buff = clCreateBuffer(context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, sizeof(float) * 4, vec, &err);     res_buff = clCreateBuffer(context, CL_MEM_WRITE_ONLY, sizeof(float) * 4, NULL, &err);      clSetKernelArg(kernel, 0, sizeof(cl_mem), &mat_buff);     clSetKernelArg(kernel, 1, sizeof(cl_mem), &vec_buff);     clSetKernelArg(kernel, 2, sizeof(cl_mem), &res_buff);      work_units_per_kernel = 4;     clEnqueueNDRangeKernel(queue, kernel, 1, NULL, &work_units_per_kernel, NULL, 0, NULL, NULL);     clEnqueueReadBuffer(queue, res_buff, CL_TRUE, 0, sizeof(float) * 4, result, 0, NULL, NULL);     printf("Result: n");     show_float4(result);     printf("Correct: n");     show_float4(correct);      if((result[0] == correct[0]) && (result[1] == correct[1])             && (result[2] == correct[2]) && (result[3] == correct[3])) {         printf("Matrix-vector multiplication successful.n");     }     else {         printf("Matrix-vector multiplication unsuccessful.n");     }      clReleaseMemObject(mat_buff);     clReleaseMemObject(vec_buff);     clReleaseMemObject(res_buff);     clReleaseKernel(kernel);     clReleaseCommandQueue(queue);     clReleaseProgram(program);     clReleaseContext(context);      return 0; }

然后编译:

 nickli@Earth:/opt/work/cl$ cd build/; make; cd .. [ 50%] Building C object CMakeFiles/example.dir/cl.c.o In file included from /usr/include/CL/cl.h:32,                  from /opt/work/cl/cl.c:12: /usr/include/CL/cl_version.h:34:9: note: #pragma message: cl_version.h: CL_TARGET_OPENCL_VERSION is not defined. Defaulting to 220 (OpenCL 2.2)    34 | #pragma message("cl_version.h: CL_TARGET_OPENCL_VERSION is not defined. Defaulting to 220 (OpenCL 2.2)")       |         ^~~~~~~ /opt/work/cl/cl.c: In function 'main': /opt/work/cl/cl.c:100:5: warning: 'clCreateCommandQueue' is deprecated [-Wdeprecated-declarations]   100 |     queue = clCreateCommandQueue(context, device, 0, &err);       |     ^~~~~ In file included from /opt/work/cl/cl.c:12: /usr/include/CL/cl.h:1781:1: note: declared here  1781 | clCreateCommandQueue(cl_context                     context,       | ^~~~~~~~~~~~~~~~~~~~ [100%] Linking C executable example [100%] Built target example 

执行:

 nickli@Earth:/opt/work/cl$ ./build/example  Program Source:  __kernel void matvec_mult(  __global float4* matrix,                              __global float4* vector,                              __global float* result) {     int i = get_global_id(0);     result[i] = dot(matrix[i], vector[0]); }  Result:  84.000000, 228.000000, 372.000000, 516.000000  Correct:  84.000000, 228.000000, 372.000000, 516.000000  Matrix-vector multiplication successful.