Ubuntu14.04 CUDA8.0 CUDN4.0 NVIDIA1080 多种深度框架(懒人三步装) - 从入门到放弃
这是一个懒人快速安装教程，1080卡有点麻烦，因为cuda需要8.0。为了安装方便直接把命令写成三个shell脚本。
代码基本是http://blog.csdn.net/langb2014/article/details/51579491，但是不完全一样。
首先准备的工作官网下载
cuda-repo-ubuntu1404-8-0-local_8.0.44-1_amd64.deb.44-1_amd64-deb.deb
cudnn-7.0-linux-x64-v40.tgz
然后就是在/home/name/下建一个soft的文件夹里面放上面两个安装包和三个.sh文件(step1.sh,step2.sh,step3.sh见后面)
由于驱动和CUDA安装完之后需要重启所以必须分成三个脚本执行，只要每次分别按顺序运行.sh脚本。
脚本中包括所有依赖库、安装框架、自带源加速、注释一些内容、修改一些内容、添加一些内容。
言归正传
前面工作准备好之后在终端运行
sudo sh ～/soft/step1.sh sudo sh ～/soft/step2.sh sudo sh ～/soft/step3.sh
三个文件： step1.sh
sudo apt-get update sudo apt-get upgrade sudo apt-get install build-essential sudo apt-get autoremove sudo apt-get install git lspci | grep -i nvidia sudo add-apt-repository ppa:graphics-drivers/ppa sudo apt-get update sudo apt-get install nvidia-367 sudo shutdown -r now
step2.sh
cat /proc/driver/nvidia/version cd ~/soft sudo dpkg -i cuda-repo-ubuntu1404*amd64*.deb sudo apt-get update sudo apt-get install cuda echo 'export PATH=/usr/local/cuda/bin:$PATH' >> ~/.bashrc echo 'export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc source ~/.bashrc nvcc -V sudo shutdown -r now
step3.sh
/usr/local/cuda/bin/cuda-install-samples-8.0.sh ~/cuda-samples
cd ~/cuda-samples/NVIDIA*Samples
make -j $(($(nproc) + 1))
bin/x86_64/linux/release/deviceQuery
cd ~/soft/
tar xvf cudnn*.tgz
cd cuda
sudo cp */*.h /usr/local/cuda/include/
sudo cp */libcudnn* /usr/local/cuda/lib64/
sudo chmod a+r /usr/local/cuda/lib64/libcudnn*
nvidia-smi
sudo apt-get install python-pip python-dev
sudo pip install six --upgrade --target="/usr/lib/python2.7/dist-packages"
export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-0.12.0-cp27-none-linux_x86_64.whl
export URL1=http://pypi.douban.com/simple
sudo pip install --upgrade $TF_BINARY_URL -i $URL1
mkdir ~/git
cd ~/git
git clone https://github.com/xianyi/OpenBLAS.git
cd OpenBLAS ####
sudo apt-get install gfortran
make FC=gfortran -j $(($(nproc) + 1))
sudo make PREFIX=/usr/local install
echo 'export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH' >> ~/.bashrc
sudo apt-get install -y libfreetype6-dev libpng12-dev
sudo pip install aws-shell -i $URL1
sudo pip install -U matplotlib ipython jupyter pandas scikit-image -i $URL1
sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler
sudo apt-get install --no-install-recommends libboost-all-dev
sudo apt-get install python-skimage ipython python-pil python-h5py ipython python-gflags python-yaml
sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev
cd ~/git http://www.90168.org/
git clone https://github.com/BVLC/caffe.git
cd caffe
cp Makefile.config.example Makefile.config
sed -i 's/# USE_CUDNN := 1/USE_CUDNN := 1/' Makefile.config
sed -i 's/# WITH_PYTHON_LAYER := 1/WITH_PYTHON_LAYER := 1/' Makefile.config
sed -i 's/BLAS := atlas/BLAS := open/' Makefile.config
sudo pip install -r python/requirements.txt -i $URL1
make all -j $(($(nproc) + 1))
make test -j $(($(nproc) + 1))
make runtest -j $(($(nproc) + 1))
make pycaffe -j $(($(nproc) + 1))
echo 'export CAFFE_ROOT=$(pwd)' >> ~/.bashrc
echo 'export PYTHONPATH=$CAFFE_ROOT/python:$PYTHONPATH' >> ~/.bashrc
source ~/.bashrc
sudo apt-get install python-numpy python-scipy python-dev python-pip python-nose g++ python-pygments python-sphinx python-nose
sudo pip install Theano -i $URL1
sudo pip install keras -i $URL1
git clone https://github.com/torch/distro.git ~/git/torch --recursive
cd ~/git/torch
bash install-deps
./install.sh
source ~/.bashrc
sudo apt-get update
sudo apt-get install -y build-essential git libatlas-base-dev libopencv-dev
git clone --recursive https://github.com/dmlc/mxnet
cd ~/soft/mxnet
cp ./make/config.mk ./
sed -i 's/USE_CUDA = 0/USE_CUDA = 1/' config.mk
sed -i '/USE_CUDA_PATH = NONE/s#NONE#/usr/local/cuda#' config.mk
make -j $(($(nproc) + 1))
