本文記錄了CUDA項目配置教程,具有一定的參考價值,感興趣的小伙伴們可以參考一下
一、新建項目
打開VS2017→ 新建項目→Win32控制臺應用程序 → “空項目”打鉤
二、調(diào)整配置管理器平臺類型
右鍵項目→ 屬性→ 配置管理器→ 全改為“x64”
三、配置生成屬性
右鍵項目 → 生成依賴項→ 生成自定義→ 勾選“CUDA 9.0XXX”
四、配置基本庫目錄
注意:后續(xù)步驟中出現(xiàn)的目錄地址需取決于你當前的CUDA版本及安裝路徑
右鍵項目→屬性→ 配置屬性→ VC++目錄→ 包含目錄,添加以下目錄:
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.0\include
C:\ProgramData\NVIDIA Corporation\CUDA Samples\v9.0\common\inc
……→ 庫目錄,添加以下目錄:
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.0\lib\x64
C:\ProgramData\NVIDIA Corporation\CUDA Samples\v9.0\common\lib\x64
五、配置CUDA靜態(tài)鏈接庫路徑
右鍵項目→ 屬性→ 配置屬性→ 鏈接器→ 常規(guī)→ 附加庫目錄,添加以下目錄:
$(CUDA_PATH_V9_0)\lib\$(Platform)
六、選用CUDA靜態(tài)鏈接庫
右鍵項目→ 屬性→ 配置屬性→ 鏈接器→ 輸入→ 附加依賴項,添加以下庫:
cublas.lib;cublas_device.lib;cuda.lib;cudadevrt.lib;cudart.lib;cudart_static.lib;cufft.lib;cufftw.lib;curand.lib;cusolver.lib;cusparse.lib;nppc.lib;nppial.lib;nppicc.lib;nppicom.lib;nppidei.lib;nppif.lib;nppig.lib;nppim.lib;nppist.lib;nppisu.lib;nppitc.lib;npps.lib;nvblas.lib;nvcuvid.lib;nvgraph.lib;nvml.lib;nvrtc.lib;OpenCL.lib;
以上為 “第三步” 中添加的庫目錄 “C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.0\lib\x64” 中的庫!
注意:
kernel32.lib;user32.lib;gdi32.lib;winspool.lib;comdlg32.lib;advapi32.lib;shell32.lib;ole32.lib;oleaut32.lib;uuid.lib;odbc32.lib;odbccp32.lib;%(AdditionalDependencies)
這些庫為原有!
七、配置源碼文件風格
右鍵源文件→ 添加→ 新建項→ 選擇 “CUDA C/C++ File”
右鍵 “xxx.cu" 源文件→ 屬性→ 配置屬性→ 常規(guī)→ 項類型→ 設置為“CUDA C/C++”
八、測試程序
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#include "cuda_runtime.h" #include "device_launch_parameters.h" #include <stdio.h> int main() { int deviceCount; cudaGetDeviceCount(&deviceCount); int dev; for (dev = 0; dev < deviceCount; dev++) { int driver_version(0), runtime_version(0); cudaDeviceProp deviceProp; cudaGetDeviceProperties(&deviceProp, dev); if (dev == 0) if (deviceProp.minor = 9999 && deviceProp.major == 9999) printf ( "\n" ); printf ( "\nDevice%d:\"%s\"\n" , dev, deviceProp.name); cudaDriverGetVersion(&driver_version); printf ( "CUDA驅(qū)動版本: %d.%d\n" , driver_version / 1000, (driver_version % 1000) / 10); cudaRuntimeGetVersion(&runtime_version); printf ( "CUDA運行時版本: %d.%d\n" , runtime_version / 1000, (runtime_version % 1000) / 10); printf ( "設備計算能力: %d.%d\n" , deviceProp.major, deviceProp.minor); printf ( "Total amount of Global Memory: %u bytes\n" , deviceProp.totalGlobalMem); printf ( "Number of SMs: %d\n" , deviceProp.multiProcessorCount); printf ( "Total amount of Constant Memory: %u bytes\n" , deviceProp.totalConstMem); printf ( "Total amount of Shared Memory per block: %u bytes\n" , deviceProp.sharedMemPerBlock); printf ( "Total number of registers available per block: %d\n" , deviceProp.regsPerBlock); printf ( "Warp size: %d\n" , deviceProp.warpSize); printf ( "Maximum number of threads per SM: %d\n" , deviceProp.maxThreadsPerMultiProcessor); printf ( "Maximum number of threads per block: %d\n" , deviceProp.maxThreadsPerBlock); printf ( "Maximum size of each dimension of a block: %d x %d x %d\n" , deviceProp.maxThreadsDim[0], deviceProp.maxThreadsDim[1], deviceProp.maxThreadsDim[2]); printf ( "Maximum size of each dimension of a grid: %d x %d x %d\n" , deviceProp.maxGridSize[0], deviceProp.maxGridSize[1], deviceProp.maxGridSize[2]); printf ( "Maximum memory pitch: %u bytes\n" , deviceProp.memPitch); printf ( "Texture alignmemt: %u bytes\n" , deviceProp.texturePitchAlignment); printf ( "Clock rate: %.2f GHz\n" , deviceProp.clockRate * 1e-6f); printf ( "Memory Clock rate: %.0f MHz\n" , deviceProp.memoryClockRate * 1e-3f); printf ( "Memory Bus Width: %d-bit\n" , deviceProp.memoryBusWidth); } return 0; } |
輸出結(jié)果:
以上就是本文的全部內(nèi)容,希望對大家的學習有所幫助,也希望大家多多支持服務器之家。
原文鏈接:https://www.cnblogs.com/wayne793377164/p/8185404.html