Learn about theCUDA Toolkit Learn aboutData centerfor technical and scientific computing Learn aboutRTXfor professional visualization Learn aboutJetsonfor AI autonomous machines If you have an older NVIDIA GPU you may find it listed on ourlegacy CUDA GPUs page ...
打开cuda的安装目录(根据自己的安装路径来):C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.0,然后将cudnn解压后对应的文件复制到C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.0对应的cuda里。(注意是路径中的文件) 4.设置系统环境变量 打开系统环境变量,可以看到在系统变量里多了两个CUDA_PA...
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3.2 解压cudnn-windows-x86_64-8.4.1.50_cuda11.6-archive.zip 将里面的3个文件夹(bin、include、lib)复制粘贴到路径D:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.7下 3.3 命令行运行 cd/dD:\ProgramFiles\NVIDIAGPUComputingToolkit\CUDA\v11.7\extras\demo_suitebandwidthTest.exedeviceQuery.exe 有两...
然后又到cudnn下载地址 https://developer.nvidia.com/rdp/cudnn-archive 下载了与cuda11.6对应的cudann了. 解压到:C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/ 下 添加环境变量到path (已更新到v12.3 2024-01-25) C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/cudnn-windows-x86_64-8.9.6....
Learn about theCUDA Toolkit Learn aboutData centerfor technical and scientific computing Learn aboutRTXfor professional visualization Learn aboutJetsonfor AI autonomous machines If you have an older NVIDIA GPU you may find it listed on ourlegacy CUDA GPUs page ...
1、CUDA官网下载: https://developer.nvidia.com/cuda-downloads 环境变量中可以酌情考虑添加 C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.2 C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.2\lib\x64 2、CUDA版本查看 ...
cd Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1 这个目录下的实际文件如第二张图中所示,有可执行文件的bin目录 然后我们切换到bin目录中去,命令是: cd bin 然后执行下面的测试命令: nvcc -V(注意V是大写) 如果安装正常的话,且组件都正常,那么会输出下面图中所示的驱动版本信息,表示安装成功。
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.6\lib\x64 3.3 CUDA 安装验证 最后,我们依旧是打开cmd,输入nvcc-V,正确的输出如下图所示: 第四步:安装 Cudnn 首先,前往cudnn 下载来下载 cudnn库,这里我们选择:cudnn v8.8.1 for CUDA 11.x。
cudnn.h 应在 C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.5\include 目录中 cudnn.lib 应在 C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.5\lib\x64 目录中 您可以运行 TensorFlow 或 PyTorch 等支持 GPU 的深度学习程序进行验证。