Installation

Dependencies

Required

  • google protobuf (>=2.5,<3)
  • blas (tested with openblas >=0.2.10)
  • cmake (>=2.6)

Optional

  • glog
  • opencv (tested with 2.4.8)
  • lmdb (tested with 0.9)
  • cuda (tested with 6.5, 7.0 and 7.5)
  • cudnn (v4 and v5)

PySINGA has additional dependencies

  • python(==2.7)
  • pip(>=1.5)
  • swig(>=3.0)
  • numpy(>=1.11.0)
  • openblas (>=0.2.10)

Users are encouraged to install the cuda and cudnn for running SINGA on GPUs to get better performance. Most of the dependent libraries could be installed via package mangers like apt-get or homebrew.

# for ubuntu users, tested on 14.04
sudo apt-get install libprotobuf-dev libopenblas-dev libopencv-dev protobuf-compiler libgoogle-glog-dev liblmdb-dev python2.7-dev python-pip python-numpy

# for Mac OS users
brew install -vd glog lmdb
brew tap homebrew/science
brew install opencv
brew install openblas
brew tap homebrew/python
brew install python
brew install numpy  --with-openblas

Install PySINGA

From wheel

After installing the dependencies for SINGA and PySINGA, please download the correct binary:

# Ubuntu/Linux 64-bit, CPU only, Python 2.7, Protobuf 2.5
$ export SINGA_WHEEL_URL=http://comp.nus.edu.sg/~dbsystem/singa/assets/file/pb2.5/singa-1.0.0-cp27-none-linux_x86_64.whl

# Ubuntu/Linux 64-bit, CPU only, Python 2.7, Protobuf 2.6
$ export SINGA_WHEEL_URL=http://comp.nus.edu.sg/~dbsystem/singa/assets/file/pb2.6/singa-1.0.0-cp27-none-linux_x86_64.whl

# Ubuntu/Linux 64-bit, GPU enabled, Python 2.7, Protobuf 2.5, CUDA toolkit 7.5 and CuDNN v5
$ export SINGA_WHEEL_URL=http://comp.nus.edu.sg/~dbsystem/singa/assets/file/pb2.5-cuda7.5-cudnn5/singa-1.0.0-cp27-none-linux_x86_64.whl

# Ubuntu/Linux 64-bit, GPU enabled, Python 2.7, Protobuf 2.6, CUDA toolkit 7.5 and CuDNN v5
$ export SINGA_WHEEL_URL=http://comp.nus.edu.sg/~dbsystem/singa/assets/file/pb2.6-cuda7.5-cudnn5/singa-1.0.0-cp27-none-linux_x86_64.whl

Then, run the following command

$ sudo pip install --upgrade $SINGA_WHEEL_URL

If you do not have sudo right, you can run pip install in a python virtual environment. Note that in python virtual environment, you may need to reset the PYTHONPATH to empty to avoid the conflicts of system path and virtual environment path.

From source

Please compile SINGA from source (see the next section) with the ‘USE_PYTHON’ option on, and then run the following commands,

# under the build directory
$ cd python
$ sudo pip install .

If you are using a virtual environment, you can ignore the sudo keyword.

Developers can build the wheel file via

# under the build directory
$ cd python
$ python setup.py bdist_wheel

The generated wheel file is under “dist” directory. To build cnmem into the wheel file, please change CMakeLists.txt by replacing ‘SHARED’ with ‘STATIC’.

Build SINGA from source

From the downloaded tar.gz file:

Extract the downloaded. If using CUDA, CNMeM needs to be fetched:

$ cd $SINGA_ROOT/lib/cnmem/
$ git clone https://github.com/NVIDIA/cnmem

From Git:

Please clone the newest code from Github and execute the following commands,

$ git clone https://github.com/apache/incubator-singa.git
$ cd incubator-singa/

If you use CUDA, then CNMeM is necessary, which could be downloaded as

$ git submodule init
$ git submodule update

Linux & MacOS

GCC (>=4.8.1) is required to compile SINGA on Linux. For Mac OS users, you can use either GCC or Clang.

In SINGA_ROOT, execute the following commands for compiling SINGA,

$ mkdir build && cd build
$ cmake ..
$ make
$ make install

Note that if you are using CUDNN and it is not installed under system default folder, you need to let cmake know the paths to CUDNN,

$ export CMAKE_INCLUDE_PATH=<path to cudnn>/include:$CMAKE_INCLUDE_PATH
$ export CMAKE_LIBRARY_PATH=<path to cudnn>/lib64:$CMAKE_LIBRARY_PATH

You can use ccmake .. to configure the compilation options including using generating python binding and changing the installation folder. If the dependent libraries are not in the system default paths, you need to export the following environment variables

export CMAKE_INCLUDE_PATH=<path to your header file folder>
export CMAKE_LIBRARY_PATH=<path to your lib file folder>

After compiling SINGA, you can run the unit tests by

$ ./bin/test_singa

You can see all the testing cases with testing results. If SINGA passes all tests, then you have successfully installed SINGA. Please proceed to try the examples!

Windows

To be added.

FAQ

  • Q: Error from running cmake .., which cannot find the dependent libraries.

    A: If you haven't installed the libraries, please install them. If you installed the libraries in a folder that is outside of the system folder, e.g. /usr/local, please export the following variables

      export CMAKE_INCLUDE_PATH=<path to your header file folder>
  export CMAKE_LIBRARY_PATH=<path to your lib file folder>

  • Q: Error from make, e.g. the linking phase

    A: If your libraries are in other folders than system default paths, you need to export the following varaibles

    $ export LIBRARY_PATH= $ export LD_LIBRARY_PATH=

  • Q: Error from header files, e.g. ‘cblas.h no such file or directory exists’

    A: You need to include the folder of the cblas.h into CPLUS_INCLUDE_PATH, e.g.,

      $ export CPLUS_INCLUDE_PATH=/opt/OpenBLAS/include:$CPLUS_INCLUDE_PATH

  • Q:While compiling SINGA, I get error SSE2 instruction set not enabled

    A:You can try following command:

      $ make CFLAGS='-msse2' CXXFLAGS='-msse2'

  • Q:I get ImportError: cannot import name enum_type_wrapper from google.protobuf.internal when I try to import .py files.

    A: You need to install the python binding of protobuf, which could be installed via

      $ sudo apt-get install protobuf

    or from source

      $ cd /PROTOBUF/SOURCE/FOLDER
  $ cd python
  $ python setup.py build
  $ python setup.py install

  • Q: When I build OpenBLAS from source, I am told that I need a Fortran compiler.

    A: You can compile OpenBLAS by

      $ make ONLY_CBLAS=1

    or install it using

      $ sudo apt-get install libopenblas-dev

  • Q: When I build protocol buffer, it reports that GLIBC++_3.4.20 not found in /usr/lib64/libstdc++.so.6.

    A9: This means the linker found libstdc++.so.6 but that library belongs to an older version of GCC than was used to compile and link the program. The program depends on code defined in the newer libstdc++ that belongs to the newer version of GCC, so the linker must be told how to find the newer libstdc++ shared library. The simplest way to fix this is to find the correct libstdc++ and export it to LD_LIBRARY_PATH. For example, if GLIBC++_3.4.20 is listed in the output of the following command,

      $ strings /usr/local/lib64/libstdc++.so.6|grep GLIBC++

    then you just set your environment variable as

      $ export LD_LIBRARY_PATH=/usr/local/lib64:$LD_LIBRARY_PATH

  • Q: When I build glog, it reports that “src/logging_unittest.cc:83:20: error: ‘gflags’ is not a namespace-name”

    A: It maybe that you have installed gflags with a different namespace such as “google”. so glog can't find ‘gflags’ namespace. Because it is not necessary to have gflags to build glog. So you can change the configure.ac file to ignore gflags.

      1. cd to glog src directory
  2. change line 125 of configure.ac  to "AC_CHECK_LIB(gflags, main, ac_cv_have_libgflags=0, ac_cv_have_libgflags=0)"
  3. autoreconf

    After this, you can build glog again.

  • Q: When using virtual environment, everytime I run pip install, it would reinstall numpy. However, the numpy would not be used when I import numpy

    A: It could be caused by the PYTHONPATH which should be set to empty when you are using virtual environment to avoid the conflicts with the path of the virtual environment.