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[ubuntu] install CUDA & cudnn
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| version mapping | |
| https://www.tensorflow.org/install/source_windows#tested_build_configurations | |
| version | |
| CUDA: 10.0 | |
| Cudnn: 7.4.2 | |
| === CUDA === | |
| Download: https://developer.nvidia.com/cuda-toolkit-archive?spm=a2c4e.10696291.0.0.7b5819a4F6rq7s | |
| $ sudo sh cuda_10.0.130_410.48_linux.run | |
| Do you accept the previously read EULA? | |
| > accept | |
| Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 410.48? | |
| > n | |
| Install the CUDA 10.0 Toolkit? | |
| > yes | |
| Enter Toolkit Location [ default is /usr/local/cuda-10.0 ]: | |
| > ENTER | |
| Do you want to install a symbolic link at /usr/local/cuda? | |
| > y | |
| Install the CUDA 10.0 Samples? | |
| > y | |
| Enter CUDA Samples Location [ default is /home/smg ]: | |
| > ENTER | |
| $ sudo vim ~/.bashrc | |
| add two line to .bashrc and save exit | |
| export PATH=/usr/local/cuda-10.0/bin${PATH:+:${PATH}} | |
| export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-10.0/lib64 | |
| reload | |
| $ source ~/.bashrc | |
| $ sudo ldconfig | |
| Test version | |
| $ nvcc -V | |
| Test CUDA | |
| $ cd ~/NVIDIA_CUDA-10.0_Samples/1_Utilities/deviceQuery/ | |
| $ sudo make | |
| $ ./deviceQuery | |
| === cudnn === | |
| Download: https://developer.nvidia.com/rdp/cudnn-archive | |
| cuDNN v7.4 for CUDA 10.0 (with tensorflow 1.14) | |
| 1.cuDNN Runtime Library for Ubuntu18.04 (Deb) | |
| 2.cuDNN Developer Library for Ubuntu18.04 (Deb) | |
| 3.cuDNN Code Samples and User Guide for Ubuntu18.04 (Deb) | |
| 4.cuDNN Library for Linux | |
| $ sudo dpkg -i libcudnn7_7.6.4.38-1+cuda10.0_amd64.deb | |
| $ sudo dpkg -i libcudnn7-dev_7.6.4.38-1+cuda10.0_amd64.deb | |
| $ sudo dpkg -i libcudnn7-doc_7.6.4.38-1+cuda10.0_amd64.deb | |
| $ tar -xvf cudnn-10.0-linux-x64-v7.6.4.38.tgz | |
| $ sudo cp cuda/include/cudnn.h /usr/local/cuda/include 注意，解压后的文件夹名称为cuda ,将对应文件复制到 /usr/local中的cuda内 | |
| $ sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64 | |
| $ sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn* | |
| Test Version - cudnn | |
| $ cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2 | |
| Test tensorflow-gpu | |
| $ import tensorflow as tf | |
| $ sess = tf.Session(config=tf.ConfigProto(log_device_placement=True)) | |
| 错误如下： | |
| /sbin/ldconfig.real: /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn.so.8 is not a symbolic link | |
| /sbin/ldconfig.real: /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_adv_train.so.8 is not a symbolic link | |
| /sbin/ldconfig.real: /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8 is not a symbolic link | |
| /sbin/ldconfig.real: /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8 is not a symbolic link | |
| /sbin/ldconfig.real: /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8 is not a symbolic link | |
| /sbin/ldconfig.real: /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_ops_train.so.8 is not a symbolic link | |
| /sbin/ldconfig.real: /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8 is not a symbolic link | |
| 解决方案： | |
| sudo ln -sf /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.0.1 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_adv_train.so.8 | |
| sudo ln -sf /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.0.1 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8 | |
| sudo ln -sf /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.0.1 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8 | |
| sudo ln -sf /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.0.1 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8 | |
| sudo ln -sf /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.0.1 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_ops_train.so.8 | |
| sudo ln -sf /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.0.1 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8 | |
| === CUDA === | |
| for ubuntu18 | |
| Tensorflow 2.4.0 | |
| Cuda 11.0 | |
| Cudnn 8 | |
| TensorRT 7.2.1.6 | |
| nvidia-driver 450 | |
| 同樣採用官網下載deb 回來安裝的方法 | |
| 到這邊 https://developer.nvidia.com/cuda-downloads | |
| 我選擇 Linux -- x86_64 -- Ubuntu -- 18.04 -- deb(local) | |
| 畫面上就會有安裝步驟，照著做就沒問題了 | |
| install guide | |
| $ wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin | |
| $ sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600 | |
| $ wget https://developer.download.nvidia.com/compute/cuda/11.0.3/local_installers/cuda-repo-ubuntu1804-11-0-local_11.0.3-450.51.06-1_amd64.deb | |
| $ sudo dpkg -i cuda-repo-ubuntu1804-11-0-local_11.0.3-450.51.06-1_amd64.deb | |
| $ sudo apt-key add /var/cuda-repo-ubuntu1804-11-0-local/7fa2af80.pub | |
| $ sudo apt-get update | |
| $ sudo apt-get -y install cuda | |
| $ sudo vim ~/.bashrc | |
| add two line to .bashrc and save exit | |
| export PATH=/usr/local/cuda-10.0/bin${PATH:+:${PATH}} | |
| export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-10.0/lib64 | |
| reload | |
| $ source ~/.bashrc | |
| $ sudo ldconfig | |
| Check version | |
| $ nvcc -V | |
| Test CUDA | |
| $ cd ~/NVIDIA_CUDA-10.0_Samples/1_Utilities/deviceQuery/ | |
| $ sudo make | |
| $ ./deviceQuery | |
| === Cudnn === | |
| Download: https://developer.nvidia.com/rdp/cudnn-archive | |
| cuDNN v7.4 for CUDA 10.0 (with tensorflow 1.14) | |
| 1.cuDNN Runtime Library for Ubuntu18.04 (Deb) | |
| 2.cuDNN Developer Library for Ubuntu18.04 (Deb) | |
| 3.cuDNN Code Samples and User Guide for Ubuntu18.04 (Deb) | |
| 4.cuDNN Library for Linux | |
| $ sudo dpkg -i libcudnn7_7.6.4.38-1+cuda10.0_amd64.deb | |
| $ sudo dpkg -i libcudnn7-dev_7.6.4.38-1+cuda10.0_amd64.deb | |
| $ sudo dpkg -i libcudnn7-doc_7.6.4.38-1+cuda10.0_amd64.deb | |
| $ tar -xvf cudnn-10.0-linux-x64-v7.6.4.38.tgz | |
| $ sudo cp cuda/include/cudnn.h /usr/local/cuda/include 注意，解压后的文件夹名称为cuda ,将对应文件复制到 /usr/local中的cuda内 | |
| $ sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64 | |
| $ sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn* | |
| Test Version - cudnn | |
| $ cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2 | |
| === TensorRT === | |
| Download: https://developer.nvidia.com/nvidia-tensorrt-7x-download | |
| $ tar -xvf TensorRT-7.2.0.14.Ubuntu-18.04.x86_64-gnu.cuda-11.0.cudnn8.0.tar.gz | |
| # sudo vim ~/.bashrc | |
| add path | |
| export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/smg/usrPack/TensorRT/TensorRT-7.2.0.14/lib | |
| $ source ~/.bashrc | |
| $ cd python | |
| $ sudo pip3 install tensorrt-7.0.0.11-cp36-none-linux_x86_64.whl | |
| $ cd uff | |
| $ sudo pip3 install uff-0.6.5-py2.py3-none-any.whl | |
| $ cd graphsurgeon | |
| $ sudo pip3 install graphsurgeon-0.4.1-py2.py3-none-any.whl | |
| $ sudo cp ./targets/x86_64-linux-gnu/lib/lib* /usr/lib/ | |
| Test TensorRT | |
| 1.下载测试数据 | |
| $ cd data/mnist | |
| $ python3 download_pgms.py | |
| 2.编译测试 | |
| $ cd samples/sampleMNIST | |
| $ make | |
| 3.运行 | |
| $ cd ../../bin | |
| $ ./sample_mnist | |
| ref. | |
| Cuda | |
| https://gitpress.io/@chchang/install-nvidia-driver-cuda-pgstrom-in-ubuntu-1804 | |
| Cudnn | |
| https://gist.github.com/alien18331/aa93e7ede6b4486cc238fdeb11e4cd72 | |
| TensorRT | |
| https://blog.csdn.net/u011681952/article/details/105973996 | |
| pip3 install launchpadlib |
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