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 ..

----------------------------------------------------------------------------------------

（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。

巴特西

编译gpu集群版caffe

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