编译gpu集群版caffe

在这个版本安装之前，要先装好opencv，openmpi等。

下载地址：https://github.com/yjxiong/caffe.git

我的opencv是2.4.12版本

编译是用了：

cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -DCUDA_CUDA_LIBRARY=/usr/local/cuda/lib64/stubs/libcuda.so -D CUDA_ARCH_BIN=5.2 -D CUDA_ARCH_PTX="" -D WITH_CUDA=ON -D WITH_TBB=ON -D BUILD_NEW_PYTHON_SUPPORT=ON -D WITH_V4L=ON -D INSTALL_C_EXAMPLES=ON -D INSTALL_PYTHON_EXAMPLES=ON -D BUILD_EXAMPLES=ON -D WITH_QT=ON -D WITH_OPENGL=ON -D ENABLE_FAST_MATH=1 -D CUDA_FAST_MATH=1 -D WITH_CUBLAS=1 -D WITH_NVCUVID:BOOL="1" .

caffe的编译是：

cmake -DUSE_MPI=ON -DMPI_CXX_COMPILER=/data/dog123/openmpi/bin/mpicxx ..

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（还是写完整些比较好）

到你要存放是目录下，使用命名（git clone https://github.com/yjxiong/caffe.git）下载软件包。

将Makefile.config.example 另存一份名为Makefile.config

修改Makefile.config，最终的样子如下：

## Refer to http://caffe.berkeleyvision.org/installation.html
# Contributions simplifying and improving our build system are welcome!

# cuDNN acceleration switch (uncomment to build with cuDNN).
 USE_CUDNN := 1

# CPU-only switch (uncomment to build without GPU support).
# CPU_ONLY := 1

# To customize your choice of compiler, uncomment and set the following.
# N.B. the default for Linux is g++ and the default for OSX is clang++
# CUSTOM_CXX := g++

# CUDA directory contains bin/ and lib/ directories that we need.
CUDA_DIR := /usr/local/cuda
# On Ubuntu 14.04, if cuda tools are installed via
# "sudo apt-get install nvidia-cuda-toolkit" then use this instead:
# CUDA_DIR := /usr

# CUDA architecture setting: going with all of them.
# For CUDA < 6.0, comment the *_50 lines for compatibility.
CUDA_ARCH := -gencode arch=compute_20,code=sm_20 \
		-gencode arch=compute_20,code=sm_21 \
		-gencode arch=compute_30,code=sm_30 \
		-gencode arch=compute_35,code=sm_35 \
		-gencode arch=compute_50,code=sm_50 \
		-gencode arch=compute_50,code=compute_50

# BLAS choice:
# atlas for ATLAS (default)
# mkl for MKL
# open for OpenBlas
BLAS := atlas
# Custom (MKL/ATLAS/OpenBLAS) include and lib directories.
# Leave commented to accept the defaults for your choice of BLAS
# (which should work)!
# BLAS_INCLUDE := /path/to/your/blas
# BLAS_LIB := /path/to/your/blas

# Homebrew puts openblas in a directory that is not on the standard search path
# BLAS_INCLUDE := $(shell brew --prefix openblas)/include
# BLAS_LIB := $(shell brew --prefix openblas)/lib

# This is required only if you will compile the matlab interface.
# MATLAB directory should contain the mex binary in /bin.
 MATLAB_DIR := /usr/local/MATLAB/R2014a
# MATLAB_DIR := /Applications/MATLAB_R2012b.app

# NOTE: this is required only if you will compile the python interface.
# We need to be able to find Python.h and numpy/arrayobject.h.
PYTHON_INCLUDE := /usr/include/python2.7 \
		/usr/lib/python2.7/dist-packages/numpy/core/include
# Anaconda Python distribution is quite popular. Include path:
# Verify anaconda location, sometimes it's in root.
# ANACONDA_HOME := $(HOME)/anaconda
# PYTHON_INCLUDE := $(ANACONDA_HOME)/include \
		# $(ANACONDA_HOME)/include/python2.7 \
		# $(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include \

# We need to be able to find libpythonX.X.so or .dylib.
PYTHON_LIB := /usr/lib
# PYTHON_LIB := $(ANACONDA_HOME)/lib

# Homebrew installs numpy in a non standard path (keg only)
# PYTHON_INCLUDE += $(dir $(shell python -c 'import numpy.core; print(numpy.core.__file__)'))/include
# PYTHON_LIB += $(shell brew --prefix numpy)/lib

# Uncomment to support layers written in Python (will link against Python libs)
 WITH_PYTHON_LAYER := 1

# Whatever else you find you need goes here.
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib

# If Homebrew is installed at a non standard location (for example your home directory) and you use it for general dependencies
# INCLUDE_DIRS += $(shell brew --prefix)/include
# LIBRARY_DIRS += $(shell brew --prefix)/lib

# Uncomment to use `pkg-config` to specify OpenCV library paths.
# (Usually not necessary -- OpenCV libraries are normally installed in one of the above $LIBRARY_DIRS.)
# USE_PKG_CONFIG := 1

BUILD_DIR := build
DISTRIBUTE_DIR := distribute

# Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171
# DEBUG := 1

# The ID of the GPU that 'make runtest' will use to run unit tests.
TEST_GPUID := 0

# enable pretty build (comment to see full commands)
Q ?= @

　　（红色部分是要核对下的）

然后在caffe目录下执行如下命令：

创建build文件夹并进入：

mkdir build

cd build

编译：

cmake -DUSE_MPI=ON -DMPI_CXX_COMPILER=/data/dog123/openmpi/bin/mpicxx ..

编译的结果是：

og@asus:/data/dog123/caffe/build$ cmake -DUSE_MPI=ON -DMPI_CXX_COMPILER=/data/dog123/openmpi/bin/mpicxx ..
-- The C compiler identification is GNU 4.7.3
-- The CXX compiler identification is GNU 4.7.3
-- Check for working C compiler: /usr/bin/cc
-- Check for working C compiler: /usr/bin/cc -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Check for working CXX compiler: /usr/bin/c++
-- Check for working CXX compiler: /usr/bin/c++ -- works
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Boost version: 1.64.0
-- Found the following Boost libraries:
--   system
--   thread
-- Looking for include file pthread.h
-- Looking for include file pthread.h - found
-- Looking for pthread_create
-- Looking for pthread_create - not found
-- Looking for pthread_create in pthreads
-- Looking for pthread_create in pthreads - not found
-- Looking for pthread_create in pthread
-- Looking for pthread_create in pthread - found
-- Found Threads: TRUE
-- Found GFlags: /usr/include
-- Found gflags  (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/libgflags.so)
-- Found Glog: /usr/include
-- Found glog    (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/libglog.so)
-- Found PROTOBUF: /usr/lib/x86_64-linux-gnu/libprotobuf.so
-- Found PROTOBUF Compiler: /usr/bin/protoc
-- Found HDF5: /usr/lib/x86_64-linux-gnu/libhdf5_hl.so;/usr/lib/x86_64-linux-gnu/libhdf5.so
-- Found LMDB: /usr/include
-- Found lmdb    (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/liblmdb.so)
-- Found LevelDB: /usr/include
-- Found LevelDB (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/libleveldb.so)
-- Found Snappy: /usr/include
-- Found Snappy  (include: /usr/include, library: /usr/lib/libsnappy.so)
-- CUDA detected: 8.0
-- Found cuDNN (include: /usr/local/cuda/include, library: /usr/local/cuda/lib64/libcudnn.so)
-- Added CUDA NVCC flags for: sm_52
-- OpenCV found (/usr/local/share/OpenCV)
-- Found Atlas: /usr/include
-- Found Atlas (include: /usr/include, library: /usr/lib/libatlas.so)
-- Found PythonInterp: /usr/bin/python2.7 (found suitable version "2.7.6", minimum required is "2.7")
-- Found PythonLibs: /usr/lib/x86_64-linux-gnu/libpython2.7.so (found suitable version "2.7.6", minimum required is "2.7")
-- Found NumPy: /usr/local/lib/python2.7/dist-packages/numpy/core/include (found suitable version "1.12.1", minimum required is "1.7.1")
-- NumPy ver. 1.12.1 found (include: /usr/local/lib/python2.7/dist-packages/numpy/core/include)
-- Boost version: 1.64.0
-- Found the following Boost libraries:
--   python
-- Found Doxygen: /usr/bin/doxygen (found version "1.8.6")
-- Found MPI_C: /data/dog123/openmpi/lib/libmpi.so
-- Found MPI_CXX: /data/dog123/openmpi/lib/libmpi.so
-- Detected Doxygen OUTPUT_DIRECTORY: ./doxygen/
-- Found Git: /usr/bin/git (found version "1.9.1")
--
-- ******************* Caffe Configuration Summary *******************
-- General:
--   Version           :   <TODO> (Caffe doesn't declare its version in headers)
--   Git               :   v0.9999-1628-gfd7458e
--   System            :   Linux
--   C++ compiler      :   /usr/bin/c++
--   Release CXX flags :   -O3 -DNDEBUG -fPIC -Wall -Wno-sign-compare -Wno-uninitialized
--   Debug CXX flags   :   -g -fPIC -Wall -Wno-sign-compare -Wno-uninitialized
--   Build type        :   Release
--
--   BUILD_SHARED_LIBS :   ON
--   BUILD_python      :   ON
--   BUILD_matlab      :   OFF
--   BUILD_docs        :   ON
--   CPU_ONLY          :   OFF
--
-- Dependencies:
--   BLAS              :   Yes (Atlas)
--   Boost             :   Yes (ver. 1.64)
--   glog              :   Yes
--   gflags            :   Yes
--   protobuf          :   Yes (ver. 2.5.0)
--   lmdb              :   Yes (ver. 0.9.10)
--   Snappy            :   Yes (ver. 1.1.0)
--   LevelDB           :   Yes (ver. 1.15)
--   OpenCV            :   Yes (ver. 2.4.12)
--   CUDA              :   Yes (ver. 8.0)
--
-- NVIDIA CUDA:
--   Target GPU(s)     :   Auto
--   GPU arch(s)       :   sm_52
--   cuDNN             :   Yes
--
-- Python:
--   Interpreter       :   /usr/bin/python2.7 (ver. 2.7.6)
--   Libraries         :   /usr/lib/x86_64-linux-gnu/libpython2.7.so (ver 2.7.6)
--   NumPy             :   /usr/local/lib/python2.7/dist-packages/numpy/core/include (ver 1.12.1)
--
-- Documentaion:
--   Doxygen           :   /usr/bin/doxygen (1.8.6)
--   config_file       :   /data/dog123/caffe/.Doxyfile
--
-- Install:
--   Install path      :   /data/dog123/caffe/build/install
--
-- Configuring done
-- Generating done
-- Build files have been written to: /data/dog123/caffe/build
dog@asus:/data/dog123/caffe/build$

　　

安装：

make all -j8 (j8 是为了加快安装速度，可以去掉)

sudo make install (注意 sudo权限)

最后就是测试：

make runtest (我这里有2个test不过，但是我还没找到原因（因为没看到错误在哪，都在输出的前面覆盖了），因为装好多遍都有2个不过，所以先将就。也就是这样，感觉自己跟一个炸弹绑在一起，我不知道它什么时候会不爽然后炸我1炸，哈哈哈哈哈)

最后就是python和matlab接口。

这2者都是caffe装之前就装好了的。

编译python接口：

添加环境变量：

vi ~/.bashrc

写入：

export PYTHONPATH=/your/path/caffe/python:$PYTHONPATH

保存，退出，执行sourc使文件生效：
source ~/.bashrc

接着在caffe目录下：

sudo make pycaffe

如果报错，点这里。一般再执行一遍上面命令即可。

最后就是：输入命令：

python

import caffe

没报错就是成功了。

编译matlab接口：

同理，在~/.bashrc中添加环境变量：

export PATH=$PATH:/usr/local/MATLAB/R2014a/bin

然后在caffe目录下执行：

sudo make matcaffe

没报错的话,就用下面命令测试下：

make matcaffe

如果报错，就点这里

嗯，就这些。