![]() If (you found your GPU Card is CUDA Supported) ' > ~/.bashrc The command decompresses the file and saves the files in the include and lib folders to the corresponding folders in the /usr/local/include/usr/local/lib directory.Check your GPU Graphic Card for the CUDA Enabled feature, the compute capability listed here for Nvidia CUDA GPUs Graphic Cards. The following command: sudo dpkg -i nccl-repo-ubuntu1604-2.1.4-ga-cuda9.1_1-1_b In this example, the operating system is Ubuntu 16.0.4, and NCCL 2.1.4 for Ubuntu 16.04 and CUDA 9 is selected. Select a version for the operating system. In this example, Download NCCL v2.1.4, for CUDA 9.1, is selected. Register for an account and log in as prompted. NCCL provides routines that are optimized to achieve PCIe, NVLink, and InfiniBand high-speed interconnection. NVIDIA Collective Communications Library (NCCL) implements multi-GPU collective communication primitives that are performance optimized for NVIDIA GPUs. The following command to decompress the file: sudo tar –xvf cudnn-9.1-linux-圆4-v7.tgz –C /usr/local - Installation is completed. Go to the directory where the downloaded file is saved and execute ![]() In this example, cuDNN v7.0.5 Library for Linux is selected and the cudnn-9.1-linux-圆4-v7.tgz file is downloaded. Select the version for your operating system. In this example, the version for CUDA 9.1 is selected. ![]() Select the version for the installed CUDA. Access cuDNN, and then click Download cuDNN. This topic describes how to configure cuDNN on Ubuntu 16.0.4. cuDNN provides highly tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. ![]() NVIDIA CUDA® Deep Neural Network library (cuDNN) is a GPU-accelerated library of primitives for deep neural networks. ![]()
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