如何使用Caffe启用多线程?

I would like to compile / configure Caffe so that when I trained an artificial neural network with it, the training is multi-threaded (CPU only, no GPU). How to enable multithreading with Caffe? I use Caffe on Ubuntu 14.04 LTS x64.

我想编译/配置Caffe，这样当我用它训练一个人工神经网络时，训练是多线程的(CPU，没有GPU)。如何使用Caffe启用多线程?我在Ubuntu 14.04 LTS x64上使用Caffe。

2 个解决方案

#1

One way is to use OpenBLAS instead of the default ATLAS. To do so,

一种方法是使用OpenBLAS而不是默认的ATLAS。要做到这一点,

1. sudo apt-get install -y libopenblas-dev
2. 安装-y libopenblas-dev。
3. Before compiling Caffe, edit Makefile.config, replace BLAS := atlas by BLAS := open
4. 在编译Caffe之前，编辑Makefile。配置，替换BLAS:= atlas by BLAS:= open。
5. After compiling Caffe, running export OPENBLAS_NUM_THREADS=4 will cause Caffe to use 4 cores.
6. 在编译了Caffe之后，运行导出OPENBLAS_NUM_THREADS=4将导致Caffe使用4个内核。

---

If interested, here is a script to install Caffe and pycaffe on a new Ubuntu 14.04 LTS x64 or Ubuntu 14.10 x64. CPU only, multi-threaded Caffe. It can probably be improved, but it's good enough for me for now:

如果有兴趣，这里有一个脚本可以在新的Ubuntu 14.04 LTS x64或Ubuntu 14.10 x64上安装Caffe和pycaffe。CPU,多线程的咖啡。它可能会有所改善，但现在对我来说已经足够好了:

# This script installs Caffe and pycaffe on Ubuntu 14.04 x64 or 14.10 x64. CPU only, multi-threaded Caffe.
# Usage: 
# 0. Set up here how many cores you want to use during the installation:
# By default Caffe will use all these cores.
NUMBER_OF_CORES=4
# 1. Execute this script, e.g. "bash compile_caffe_ubuntu_14.04.sh" (~30 to 60 minutes on a new Ubuntu).
# 2. Open a new shell (or run "source ~/.bash_profile"). You're done. You can try 
#    running "import caffe" from the Python interpreter to test.

#http://caffe.berkeleyvision.org/install_apt.html : (general install info: http://caffe.berkeleyvision.org/installation.html)
cd
sudo apt-get update
#sudo apt-get upgrade -y # If you are OK getting prompted
sudo DEBIAN_FRONTEND=noninteractive apt-get upgrade -y -q -o Dpkg::Options::="--force-confdef" -o Dpkg::Options::="--force-confold" # If you are OK with all defaults

sudo apt-get install -y libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev
sudo apt-get install -y --no-install-recommends libboost-all-dev
sudo apt-get install -y libatlas-base-dev 
sudo apt-get install -y python-dev 
sudo apt-get install -y python-pip git

# For Ubuntu 14.04
sudo apt-get install -y libgflags-dev libgoogle-glog-dev liblmdb-dev protobuf-compiler 

# LMDB
# https://github.com/BVLC/caffe/issues/2729: Temporarily broken link to the LMDB repository #2729
#git clone https://gitorious.org/mdb/mdb.git
#cd mdb/libraries/liblmdb
#make && make install 

git clone https://github.com/LMDB/lmdb.git 
cd lmdb/libraries/liblmdb
sudo make 
sudo make install

# More pre-requisites 
sudo apt-get install -y cmake unzip doxygen
sudo apt-get install -y protobuf-compiler
sudo apt-get install -y libffi-dev python-dev build-essential
sudo pip install lmdb
sudo pip install numpy
sudo apt-get install -y python-numpy
sudo apt-get install -y gfortran # required by scipy
sudo pip install scipy # required by scikit-image
sudo apt-get install -y python-scipy # in case pip failed
sudo apt-get install -y python-nose
sudo pip install scikit-image # to fix https://github.com/BVLC/caffe/issues/50


# Get caffe (http://caffe.berkeleyvision.org/installation.html#compilation)
cd
mkdir caffe
cd caffe
wget https://github.com/BVLC/caffe/archive/master.zip
unzip -o master.zip
cd caffe-master

# Prepare Python binding (pycaffe)
cd python
for req in $(cat requirements.txt); do sudo pip install $req; done
echo "export PYTHONPATH=$(pwd):$PYTHONPATH " >> ~/.bash_profile # to be able to call "import caffe" from Python after reboot
source ~/.bash_profile # Update shell 
cd ..

# Compile caffe and pycaffe
cp Makefile.config.example Makefile.config
sed -i '8s/.*/CPU_ONLY := 1/' Makefile.config # Line 8: CPU only
sudo apt-get install -y libopenblas-dev
sed -i '33s/.*/BLAS := open/' Makefile.config # Line 33: to use OpenBLAS
# Note that if one day the Makefile.config changes and these line numbers change, we're screwed
# Maybe it would be best to simply append those changes at the end of Makefile.config 
echo "export OPENBLAS_NUM_THREADS=($NUMBER_OF_CORES)" >> ~/.bash_profile 
mkdir build
cd build
cmake ..
cd ..
make all -j$NUMBER_OF_CORES # 4 is the number of parallel threads for compilation: typically equal to number of physical cores
make pycaffe -j$NUMBER_OF_CORES
make test
make runtest
#make matcaffe
make distribute

# Bonus for other work with pycaffe
sudo pip install pydot
sudo apt-get install -y graphviz
sudo pip install scikit-learn

# At the end, you need to run "source ~/.bash_profile" manually or start a new shell to be able to do 'python import caffe', 
# because one cannot source in a bash script. (http://*.com/questions/16011245/source-files-in-a-bash-script)

I have placed this script on GitHub:
https://github.com/Franck-Dernoncourt/caffe_demos/tree/master/caffe_installation .

我已经把这个脚本放在GitHub上:https://github.com/franck - dernoncourt/_demos/tree/master/_installation。

#2

While building caffe, you have to add the -fopenmp to the CXXFLAGS and LINKFLAGS to support OPENMP. If you have a flag named OPENMP in the Makefil.config, you can simply set that to 1. You can use either OPENBLAS or Intel MKL BLAS library. While building the OPENBLAS you need to set USE_OPENMP=1 flag so that it supports OPENMP. After building caffe, please export the number of threads you want to use during runtime by setting up OMP_NUM_THREADS=n where n is the number of threads you want. Here is a good discussion related to multi-threading in Caffe: https://github.com/BVLC/caffe/pull/439

在构建caffe时，您必须将-fopenmp添加到CXXFLAGS和LINKFLAGS以支持OPENMP。如果在Makefil中有一个名为OPENMP的标记。你可以把它设为1。您可以使用OPENBLAS或Intel MKL BLAS库。在构建OPENBLAS时，您需要设置USE_OPENMP=1标志，以便它支持OPENMP。在构建caffe之后，请通过设置OMP_NUM_THREADS=n来导出您想要在运行时使用的线程数量，其中n是您想要的线程数。这里有一个关于Caffe中的多线程的很好的讨论:https://github.com/bvlc//439。