C++ 初学者 CUDA 程序中未解析的外部符号
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/2061715/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
Unresolved external symbols in beginners CUDA program
提问by Mr Bell
I create a new Win32 Console App as an empty project I am running Windows 7 64bit with Visual Studio 2008 C++. I am trying to get the sample code from the bottom of this article to build: http://www.ddj.com/architect/207200659
我创建了一个新的 Win32 控制台应用程序作为一个空项目，我正在使用 Visual Studio 2008 C++ 运行 Windows 7 64 位。我试图从本文底部获取示例代码来构建：http: //www.ddj.com/architect/207200659
I add CUDA Build Rule v2.3.0 to the project's custom build rules. It is the only thing with a checkbox in the available rule files list
我将 CUDA Build Rule v2.3.0 添加到项目的自定义构建规则中。它是可用规则文件列表中唯一带有复选框的东西
I create moveArrays.cu in the Source Files (folder/filter???)
我在源文件（文件夹/过滤器？？？）中创建了 moveArrays.cu
In that file I add the following code:
在该文件中，我添加了以下代码：
// moveArrays.cu
//
// demonstrates CUDA interface to data allocation on device (GPU)
// and data movement between host (CPU) and device.
#include <stdio.h>
#include <assert.h>
#include <cuda.h>
int main(void)
{
float *a_h, *b_h; // pointers to host memory
float *a_d, *b_d; // pointers to device memory
int N = 14;
int i;
// allocate arrays on host
a_h = (float *)malloc(sizeof(float)*N);
b_h = (float *)malloc(sizeof(float)*N);
// allocate arrays on device
cudaMalloc((void **) &a_d, sizeof(float)*N);
cudaMalloc((void **) &b_d, sizeof(float)*N);
// initialize host data
for (i=0; i<N; i++) {
a_h[i] = 10.f+i;
b_h[i] = 0.f;
}
// send data from host to device: a_h to a_d
cudaMemcpy(a_d, a_h, sizeof(float)*N, cudaMemcpyHostToDevice);
// copy data within device: a_d to b_d
cudaMemcpy(b_d, a_d, sizeof(float)*N, cudaMemcpyDeviceToDevice);
// retrieve data from device: b_d to b_h
cudaMemcpy(b_h, b_d, sizeof(float)*N, cudaMemcpyDeviceToHost);
// check result
for (i=0; i<N; i++)
assert(a_h[i] == b_h[i]);
// cleanup
free(a_h); free(b_h);
cudaFree(a_d); cudaFree(b_d);
}
When I build I get these errors:
当我构建时，我收到这些错误：
1>------ Build started: Project: CUDASandbox, Configuration: Debug x64 ------ 1>Linking... 1>moveArrays.cu.obj : error LNK2019: unresolved external symbol cudaFree referenced in function main 1>moveArrays.cu.obj : error LNK2019: unresolved external symbol cudaMemcpy referenced in function main 1>moveArrays.cu.obj : error LNK2019: unresolved external symbol cudaMalloc referenced in function main 1>moveArrays.cu.obj : error LNK2019: unresolved external symbol __cudaUnregisterFatBinary referenced in function __cudaUnregisterBinaryUtil 1>moveArrays.cu.obj : error LNK2019: unresolved external symbol __cudaRegisterFatBinary referenced in function __sti____cudaRegisterAll_45_tmpxft_00001264_00000000_6_moveArrays_cpp1_ii_main 1>D:\Stuff\Programming\Visual Studio 2008\Projects\CUDASandbox\x64\Debug\CUDASandbox.exe : fatal error LNK1120: 5 unresolved externals 1>Build log was saved at "file://d:\Stuff\Programming\Visual Studio 2008\Projects\CUDASandbox\CUDASandbox\x64\Debug\BuildLog.htm" 1>CUDASandbox - 6 error(s), 0 warning(s) ========== Build: 0 succeeded, 1 failed, 0 up-to-date, 0 skipped ==========
I can compile and run the example CUDA programs that came with the SDK. I know I am missing something simple here, but what is it?
我可以编译和运行 SDK 附带的示例 CUDA 程序。我知道我在这里遗漏了一些简单的东西，但它是什么？
回答by sand
回答by betontalpfa
Two things are needed:
需要做两件事：
Add CUDA path:
Go: "Configuration Properties->Linker->General->Additional Libary Directories" and add$(CudaToolkitLibDir)to the list.Add CUDA runtime library:
Go: "Solution Properties->Linker->Input->Additional Dependencies" and addcudart.libto the list.
添加CUDA路径：
转到：“配置属性->链接器->常规->附加库目录”并添加$(CudaToolkitLibDir)到列表中。添加 CUDA 运行时库：
转到：“解决方案属性->链接器->输入->附加依赖项”并添加cudart.lib到列表中。
回答by fslichen
In visual studio 2019:
在视觉工作室 2019 中：
Double check the availability of CUDA_PATH environment variable.
仔细检查 CUDA_PATH 环境变量的可用性。
Configuration Properties -> VC++ Directories -> Include Directories -> Add $(CUDA_PATH)\include
配置属性 -> VC++ 目录 -> 包含目录 -> 添加 $(CUDA_PATH)\include
Configuration Properties -> VC++ Directories -> Library Directories -> Add $(CUDA_PATH)\lib\x64
配置属性 -> VC++ 目录 -> 库目录 -> 添加 $(CUDA_PATH)\lib\x64
Configuration Properties -> Linker -> Input -> Additional Dependencies -> Add .lib files under $(CUDA_PATH)\lib\x64 and ignore existing .lib files.
配置属性 -> 链接器 -> 输入 -> 附加依赖项 -> 在 $(CUDA_PATH)\lib\x64 下添加 .lib 文件并忽略现有的 .lib 文件。
