1

构建日志：

-------------- Clean: Release in OffloadTest (compiler: GNU GCC Compiler)---------------

Cleaned "OffloadTest - Release"

-------------- Build: Release in OffloadTest (compiler: GNU GCC Compiler)---------------

g++ -Wall -m64 -fopenmp -foffload=nvptx-none -fno-stack-protector -O2 -fopenmp -foffload=nvptx-none -fcf-protection=none -fno-stack-protector  -c /home/david/CBProjects/OffloadTest/main.cpp -o obj/Release/main.o
g++  -o bin/Release/OffloadTest obj/Release/main.o  -m64 -lgomp -s -lgomp  
/usr/bin/ld: /tmp/ccfvsLgk.crtoffloadtable.o:(.rodata+0x0): undefined reference to `__offload_func_table'
/usr/bin/ld: /tmp/ccfvsLgk.crtoffloadtable.o:(.rodata+0x8): undefined reference to `__offload_funcs_end'
/usr/bin/ld: /tmp/ccfvsLgk.crtoffloadtable.o:(.rodata+0x10): undefined reference to `__offload_var_table'
/usr/bin/ld: /tmp/ccfvsLgk.crtoffloadtable.o:(.rodata+0x18): undefined reference to `__offload_vars_end'
collect2: error: ld returned 1 exit status
Process terminated with status 1 (0 minute(s), 0 second(s))
5 error(s), 0 warning(s) (0 minute(s), 0 second(s))

我已经加载了以下内容（带有描述）：

Gcc-9-offload-nvptx
    Description: The package provides offloading support for NVidia PTX. OpenMP and OpenACC programs linked with -fopenmp will by default add PTX code into the binaries, which can be offloaded to NVidia PTX capable devices if available.
Gcc-offload-nvptx
    Description: This package contains libgomp plugin for offloading to NVidia PTX. The plugin needs libcuda.so.1 shared library that has to be installed separately.
Nvptx-tools
    Description: This tool consists of nptx-non-as: "assembler" for PTX, nvptx-none-ld: "linker" for PTX. Additionally, the following symlinks are installed: nvptx-none-ar: link to the GNU/Linux host system's ar, nvptx-none-ranlib: link to the GNU/Linux host system's ranlib

我已经验证 libcuda.so.1 位于 /lib/x86_64-linux-gnu

该脚本很简单，只是一个帮助我卸载和运行的示例。如果我取出“目标”关键字，效果很好

#include <iostream>
#include <omp.h>

using namespace std;
#define iSize 200000
long *A, *B;

int main()
{
   A = new long[iSize];
   B = new long[iSize];
   long sum = 0;
   double dStart, dEnd;
   int iNumberOfDevices = omp_get_num_devices();
   int iInitialDevice = omp_get_initial_device(); // device number for host computer
   int iDeviceNumber = omp_get_default_device();

   dStart = omp_get_wtime();
#pragma omp parallel for
   for (long i=0; i<iSize; i++)
   {
      A[i] = i;
      B[i] = i+1;
   }
#pragma omp target parallel for reduction(+:sum)
   for (long i=0; i<iSize; i++)
   {
      for (long j=0; j<iSize; j++)
      {
         sum += 3 * A[i] - B[j];
      }
   }
   dEnd = omp_get_wtime();
   double dtime = dEnd - dStart;
   cout << "Number of devices = " << iNumberOfDevices << endl;
   cout << "Device number = " << iDeviceNumber << endl;
   cout << "Initial Device number (host processor) = " << iInitialDevice << endl;
   cout << endl;
   cout << "Sum = " << sum << endl;
   cout << "Processing time = " << dtime << " Seconds" << endl;
}

任何帮助表示赞赏。

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1 回答 1

0

要解析undefined references，请指定（如果这不是默认值，则-fopenmp可能再次指定）而不是（顺便说一句，重复）。-foffload=nvptx-none-lgomp

我认为还缺少一些omp target data（或类似的）指令来在设备上设置A和B数组？

于 2021-07-22T09:11:04.647 回答