Ubuntu16.04 安装配置Caffe(GPU版)

1. 安装相关依赖项

 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 libopenblas-dev liblapack-dev libatlas-base-dev
 sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev

2.安装CUDA

在终端下输入：

sudo gedit /etc/modprobe.d/blacklist.conf

输入密码后在最后一行加上 blacklist nouveau . 这里是将Ubuntu自带的显卡驱动加入黑名单。

在终端输入：

sudo update-initramfs -u 

然后重启电脑~记住一定要重启电脑，不然后面的驱动会安装失败的。

这里要尤其注意，安装显卡驱动要先切换到文字界面，(按Ctrl+Alt+F1~F6).所以，启动电脑后，先进入字符界面。

下载cuda

https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1604&target_type=runfilelocal

然后，输入命令：

sudo service lightdm stop

（2）下载完成后执行以下命令（我用的是cuda7.5）：

1 sudo chmod 777 cuda_7.5.44_linux.run
2 sudo ./cuda_7.5.44_linux.run

按照提示安装，注意这里会提示是否安装nvidia驱动，记住需要选择是，因为我们之前没有安装驱动。
安装完成之后，注意需要修改bashrc文件
可以编译sample文件夹中的文件测试，运行cuda/samples/1_Utilities/deviceQuery/deviceQuery
安装成功的话会有相关的信息提示。

./deviceQuery Starting...

 CUDA Device Query (Runtime API) version (CUDART static linking)

Detected 1 CUDA Capable device(s)

Device 0: "GeForce GTX 1080"
  CUDA Driver Version / Runtime Version          9.2 / 9.2
  CUDA Capability Major/Minor version number:    6.1
  Total amount of global memory:                 8112 MBytes (8505524224 bytes)
  (20) Multiprocessors, (128) CUDA Cores/MP:     2560 CUDA Cores
  GPU Max Clock rate:                            1772 MHz (1.77 GHz)
  Memory Clock rate:                             5005 Mhz
  Memory Bus Width:                              256-bit
  L2 Cache Size:                                 2097152 bytes
  Maximum Texture Dimension Size (x,y,z)         1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
  Maximum Layered 1D Texture Size, (num) layers  1D=(32768), 2048 layers
  Maximum Layered 2D Texture Size, (num) layers  2D=(32768, 32768), 2048 layers
  Total amount of constant memory:               65536 bytes
  Total amount of shared memory per block:       49152 bytes
  Total number of registers available per block: 65536
  Warp size:                                     32
  Maximum number of threads per multiprocessor:  2048
  Maximum number of threads per block:           1024
  Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
  Max dimension size of a grid size    (x,y,z): (2147483647, 65535, 65535)
  Maximum memory pitch:                          2147483647 bytes
  Texture alignment:                             512 bytes
  Concurrent copy and kernel execution:          Yes with 2 copy engine(s)
  Run time limit on kernels:                     Yes
  Integrated GPU sharing Host Memory:            No
  Support host page-locked memory mapping:       Yes
  Alignment requirement for Surfaces:            Yes
  Device has ECC support:                        Disabled
  Device supports Unified Addressing (UVA):      Yes
  Device supports Compute Preemption:            Yes
  Supports Cooperative Kernel Launch:            Yes
  Supports MultiDevice Co-op Kernel Launch:      Yes
  Device PCI Domain ID / Bus ID / location ID:   0 / 75 / 0
  Compute Mode:
     < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >

deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 9.2, CUDA Runtime Version = 9.2, NumDevs = 1
Result = PASS

3 安装cudnn

登录官网：https://developer.nvidia.com/rdp/cudnn-download ，下载对应 cuda 版本且 linux 系统的 cudnn 压缩包，注意官网下载 cudnn 需要注册帐号并登录

 tar -xzvf cudnn-6.5-linux-R1.tgz
 cd cudnn-6.5-linux-R1
 sudo cp lib* /usr/local/cuda/lib64/
 sudo cp cudnn.h /usr/local/cuda/include/
cd /usr/local/cuda/lib64/
sudo rm -rf libcudnn.so libcudnn.so.5    #删除原有动态文件
sudo ln -s libcudnn.so.5.1.10 libcudnn.so.5  #生成软衔接（注意这里要和自己下载的cudnn版本对应，可以在/usr/local/cuda/lib64下查看自己libcudnn的版本）
sudo ln -s libcudnn.so.5 libcudnn.so      #生成软链接

#需要和自己的版本号对应
sudo cp /usr/local/cuda-8.0/lib64/libcudart.so.8.0 /usr/local/lib/libcudart.so.8.0 && sudo ldconfig
sudo cp /usr/local/cuda-8.0/lib64/libcublas.so.8.0 /usr/local/lib/libcublas.so.8.0 && sudo ldconfig

sudo cp /usr/local/cuda-8.0/lib64/libcurand.so.8.0 /usr/local/lib/libcurand.so.8.0
sudo cp /usr/local/cuda-8.0/lib64/libcudnn.so.5 /usr/local/lib/libcudnn.so.5

4 安装caffe

接下来就需要正式的安装caffe了。
首席爱呢clone下caffe的github目录来

git clone https://github.com/BVLC/caffe.git

然后修改makefile

cp Makefile.config.exemple Makefile.config
#修改makefile和makefile.config 减少出错
#修改Makefile.config
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial/

#修改Makefile文件
将：
LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_hl hdf5
改为：
LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_serial_hl hdf5_serial

#安装
make all -j12#为你的cpu数目
make test
make runtest

some question:
one: libcudart.so is not found
sloved: sudo ldconfig /usr/local/cuda/lib64
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