注：系统安装好后，先确认kernel kernel-headers kernel-devel kernel-firmware四个包的版本要相同

#rpm -qa |grep kernel

注： 先修改yum配置文件 /etc/yum.conf 修改 keepcache=1

1. 安装库

yum -y install epel-release.noarch

(wget http://pkgs.repoforge.org/rpmforge-release/rpmforge-release-0.5.3-1.el6.rf.x86_64.rpm)

rpm --import http://apt.sw.be/RPM-GPG-KEY.dag.txt

rpm -K rpmforge-release-0.5.3-1.el6.rf.*.rpm

rpm -ivh rpmforge-release-0.5.3-1.el6.rf.*.rpm rpmforge-releaser

2、JDK安装

tar –xf jdk-7u25-linux-x64.tar.gz && mv jdk1.7.0_25/ jdk1.7 mv jdk1.7/ /opt

vim /etc/profile

export JAVA_HOME=/opt/jdk1.7

export JAVA_BIN=/opt/jdk1.7/bin

export PATH=$PATH:$JAVA_HOME/bin

export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar

export PATH=$JAVA_HOME/bin:$JRE_HOME/bin:$PATH

source /etc/profile

3、编译安装python2.7（centOS6上用的是python2.6）

python官网：https://www.python.org/downloads/release/python-279/

替换python要在安装boost依赖之前

# wget https://www.python.org/ftp/python/2.7.9/Python-2.7.9.tgz

编译安装python2.7（必须先安装zlib与openssl的包再执行编译）

先安装gcc zlib openssl 等包

tar -xvf Python-2.7.9.tgz -C /usr/src

cd /usr/src/Python-2.7.9

./configure --enable-shared

make -j12

make altinstall

（altinstall在安装时会区分已存在的版本）(解决libpython2.7.so.1.0办法：vi /etc/ld.so.conf 添加/usr/local/lib，然后ldconfig)

替换系统中的python

ls -l `which python python2 python2.6`

rm /usr/bin/python

ln -s -f /usr/local/bin/python2.7 /usr/bin/python

保持yum可用性

vim /usr/bin/yum

#!/usr/bin/python 改为 #!/usr/bin/python2.6

4、安装pip

curl -O https://bootstrap.pypa.io/get-pip.py # 得到一个get-pip.py

python get-pip.py

Installing collected packages: pip, setuptools, wheel

Successfully installed pip-7.1.0 setuptools-18.0.1 wheel-0.24.0

（必须先安装openssl-devel与zlib的包，再执行python编译，若执行该命令的时候出现红色cann't remove easy-install.pth的提醒，但目录下又无此文件，可新建后再次执行一遍命令，安装系统的时候最好把开发工具的选项给勾上，出现“Successfully installed pip-6.0.8 setuptools-14.3.1为安装成功”）

5、安装cuda-6.5及驱动

wget http://developer.download.nvidia.com/compute/cuda/repos/rhel6/x86_64/cuda-repo-rhel6-6.5-14.x86_64.rpm

rpm -ivh cuda-repo-rhel6-6.5-14.x86_64.rpm

yum install cuda-6-5

GTX 660显卡装cuda后会导致Xorg狂奔，直至系统死机，需要将/etc/inittab中的启动级别改为3

注，驱动包文件结构不对，导致nvidia_uvm.ko模块无法编译，需手动解决

cd /var/lib/dkms/nvidia/346.46

cp -rv /usr/src/nvidia-346.46 build

如果使用yum 方式安装的使用下载下的驱动包升级下

chmod +x NVIDIA-Linux-x86_64-346.72.run

./NVIDIA-Linux-x86_64-346.72.run

重启后，dkms会在开机时完成nvidia_uvm.ko的编译

/lib/modules/版本号/extra/下有两个包：nvidia.ko nvidia_uvm.ko

lsmod|grep nvidia

vi /etc/rc.local #编辑该文件

modprobe nvidia_uvm #添加该条

5.1 run包安装方式

chmod +x cuda_6.5.19_linux_64.run

./ cuda_6.5.19_linux_64.run

6、安装blas

yum -y install blas.x86_64 blas-devel.x86_64

atlas.x86_64 atlas-devel.x86_64 atlas-sse3.x86_64 atlas-sse3-devel.x86_64

7、安装opencv

yum -y install ant.x86_64 gcc.x86_64 gcc-c++.x86_64 cmake.x86_64 git.x86_64 pkgconfig.x86_64 gtk2.x86_64 gtk2-devel.x86_64 libdc1394.x86_64 libdc1394-devel.x86_64 libjpeg-turbo.x86_64 libjpeg-turbo-devel.x86_64 libpng.x86_64 libpng-devel.x86_64 libtiff.x86_64 libtiff-devel.x86_64 jasper.x86_64 jasper-libs.x86_64 jasper-devel.x86_64 yasm.x86_64 yasm-devel.x86_64

pip install numpy

安装ffmpeg： #此包不需要通过yum安装，yum安装版本不对

tar -xf ffmpeg-2.6.1.tar.bz2 -C /usr/src

cd /usr/src/ffmpeg-2.6.1/

./configure --enable-shared #要以共享库方式配置，否则opencv编译时链接静态库会出错

make -j12 && make install

unzip opencv-2.4.9

cd opencv-2.4.9

mkdir release && cd release

修改源文件NCVPixelOperations.hpp，

文件替换到opencv路径下的modules/gpu/src/nvidia/core/NCVPixelOperations.hpp

配置环境变量：

vim /etc/profile.d/custom.sh 配置完成source /etc/profile.d/custom.sh

#!/bin/bash

export PATH=/usr/local/MATLAB/R2014a/bin:/usr/local/cuda-6.5/bin:$PATH

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/boost-1.55.0/lib:/usr/local/cuda-6.5/lib64:/opt/caffe-master/build/lib:/usr/lib64/atlas

export LIBRARY_PATH=$LIBRARY_PATH:/usr/local/boost-1.55.0/lib:/usr/local/cuda-6.5/lib64:/opt/caffe-master/build/lib:/usr/lib64/atlas

export C_INCLUDE_PATH=$C_INCLUDE_PATH:/usr/local/boost-1.55.0/include:/usr/local/cuda-6.5/include:/opt/caffe-master/build/src:/opt/caffe-master/include

export CPLUS_INCLUDE_PATH=$CPLUS_INCLUDE_PATH:/usr/local/boost-1.55.0/include:/usr/local/cuda-6.5/include:/opt/caffe-master/build/src:/opt/caffe-master/include

export PYTHONPATH=$PYTHONPATH:/opt/caffe-master/python

export HISTTIMEFORMAT="%F %T "

cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local ..

make –j12

make install

8、安装boost-1.55（1.56不兼容）

yum -y install libicu.x86_64 libicu-devel.x86_64 bzip2-libs.x86_64 bzip2-devel.x86_64

tar –xf boost_1_55_0.tar.gz && cd boost_1_55_0

./bootstrap.sh

./b2

./b2 install

运行./b2 install命令，默认安装在/usr/local/lib目录下，头文件在/usr/local/include/boost目录下

9、安装caffe其他依赖：

yum -y install snappy.x86_64 snappy-devel.x86_64 hdf5.x86_64 hdf5-devel.x86_64 epel-release leveldb.x86_64 leveldb-devel.x86_64 libgfortran.x86_64

------ 编译安装protobuf-2.5.0 protobuf-2.5.0

------ tar -xvf protobuf-2.5.0.tar.gz

------ cd /usr/src/protobuf-2.5.0

./configure

make

make check

make install

------ export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH

10、编译安装caffe其他依赖包

glog

wget https://google-glog.googlecode.com/files/glog-0.3.3.tar.gz

tar zxvf glog-0.3.3.tar.gz

cd glog-0.3.3

./configure

make && make install

gflags

wget https://github.com/schuhschuh/gflags/archive/master.zip

unzip gflags-master.zip

cd gflags-master

mkdir build && cd build

export CXXFLAGS="-fPIC" && cmake .. && make VERBOSE=1

make && make install

lmdb

git clone git://gitorious.org/mdb/mdb.git

tar –xf lmdb.tar

cd mdb/libraries/liblmdb

make && make install #若提示man1错误，手动建立一个

mkdir -p /usr/local/man/man1

11、将matlab上传至服务器，通过图形方式安装

安装秘钥12345-67890-12345-67890

安装完成后导入lic文件，然后替换libmwservices.so到

/usr/local/MATLAB/R2014a/bin/glnxa64/进行覆盖，结束安装。

12、解决python依赖

pip install 'six>=1.3'

easy_install -U distribute

pip2.7 install PIL --allow-external PIL --allow-unverified PIL

解包caffe-master.zip，并将该包移至opt目录

cd /opt/caffe-master/python

for i in $(cat requirements.txt); do pip install $i; done #需要多执行几遍

注：会出现一个报错，关于PIL.Image >= 1.1.7，则可使用命令pip install 'PIL' 进行安装

后再次执行以上的for循环语句，需要将python升级至2.7以上版本（安装及注意事项下：）

13、安装caffe

修改caffe-master/Makefile.config文件，增加如下几句

cp /opt/caffe-master/Makefile.config.example Makefile.config

vim Makefile.config

MATLAB_DIR := /usr/local/MATLAB/R2014a/

BLAS := atlas

BLAS_LIB := /usr/lib64/atlas

PYTHON_INCLUDE := /usr/include/python2.7

/usr/local/lib/python2.7/site-packages/numpy/core/include

/usr/local/include/python2.7

执行 ldconfig

make all -j12

make –j12 pycaffe

make –j12 matcaffe

make test –j12

make runtest –j12

如果matlab要使用静态编译libprotobuf.a的话，修改Makefile

在MATLAB_CXXFLAGS项上添加-static参数即可

但使用动态库的matlab模型可能不可用

若一切没有问题，至此caffe环境安装结束，待测试。

以下为可选部分

编译安装protobuf-2.5.0 protobuf-2.5.0

tar -xvf protobuf-2.5.0.tar.gz

cd /usr/src/protobuf-2.5.0

./configure

make

make check

make install

export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH

继续安装protobuf的python模块(如果不用python，可跳过这一步)

#cd ./python

#python setup.py build

#python setup.py test

#python setup.py install

安装cudnn

LINUX

cd <installpath>

export LD_LIBRARY_PATH=`pwd`:$LD_LIBRARY_PATH

Add <installpath> to your build and link process by adding -I<installpath> to your compile line and -L<installpath> -lcudnn to your link line.

a. 编辑确保Makefile.config,启用GPU “# CPU_ONLY := 1”,并设置 “USE_CUDNN := 1”。

b. 安装cuDNN

tar -xzvf cudnn-6.5-linux-R1.tgz

cd cudnn-6.5-linux-R1

cp lib* /usr/local/cuda-6.5/lib64/

cp cudnn.h /usr/local/cuda-6.5/include/

cd /usr/local/cuda-6.5/lib64/

rm -rf libcudnn.so libcudnn.so.6.5

chmod u=rwx,g=rx,o=rx libcudnn.so.6.5.18

ln -s libcudnn.so.6.5.18 libcudnn.so.6.5

ln -s libcudnn.so.6.5 libcudnn.so

ldconfig

注1：将相关的头文件，库文件放到profile中定义的系统路径里即可，matlab的mex运行时需要加载对应库

caffe编译时也可在Makefile.config中修改，添加cuDNN的路径/cache/INSTALL_cuDNN/cudnn-6.5-linux-R1

INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /cache/INSTALL_cuDNN/cudnn-6.5-linux-R1

LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /cache/INSTALL_cuDNN/cudnn-6.5-linux-R1

注2：在使用tesla-c2050显卡时，需要在Makefile.config里改如下几个地方：

PYTHON_LIB := /usr/lib64 #原为PYTHON_LIB := /usr/lib

LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib64 /usr/lib64 #原为如下：

LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib

注3：protobuf手动安装，不需要通过yum，yum安装版本不对，make runtest会报错，使用protobuf2.5的版本，安装方式见上，在编译caffe前安装好后再进行编译。

包：咖啡环境需要上传的包：gflags-master.zip、opencv-2.4.9.zip、boost_1_55_0.tar.gz、caffe-master.zip、glog-0.3.3.tar.gz、protobuf-2.5.0.tar.gz、cuda-repo-rhel6-6.5-14.x86_64.rpm、jdk-7u25-linux-x64.tar.gz、lmdb.tar、Python-2.7.9.tgz、 ffmpeg-2.6.1.tar.bz2、

rpmforge-release-0.5.3-1.el6.rf.x86_64.rpm、NVIDIA-Linux-x86_64-346.72.run、

NCVPixelOperations.hpp、matlab文件夹