Caffe GPU Installation (2015-05-14)

install.sh

#!/bin/bash

wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64/cuda-repo-ubuntu1404_7.0-28_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1404_7.0-28_amd64.deb
sudo apt-add-repository multiverse
sudo apt-get update
sudo apt-get install -y --no-install-recommends \
    linux-image-extra-virtual linux-image-extra-$(uname -r) linux-headers-virtual linux-headers-$(uname -r) \
    cuda \
    git build-essential \
    libopenblas-dev libprotobuf-dev libboost-all-dev libleveldb-dev libopencv-dev libsnappy-dev libhdf5-serial-dev libgflags-dev libgoogle-glog-dev liblmdb-dev protobuf-compiler python-dev libffi-dev \
    ipython python-pip python-pil cython python-numpy python-scipy python-skimage python-sklearn python-matplotlib python-h5py python-leveldb python-networkx python-nose python-pandas python-protobuf python-gflags graphviz
sudo bash -c 'echo /usr/local/cuda/lib64 > /etc/ld.so.conf.d/cuda.conf'
sudo ldconfig

sudo bash -c 'echo "exec nvidia-smi" > /etc/rc2.d/S99nvidia-probe'
sudo chmod 755 /etc/rc2.d/S99nvidia-probe
sudo nvidia-smi

cd
git clone https://github.com/BVLC/caffe
cd caffe
git checkout 2382b096
sudo pip install -r python/requirements.txt
wget -O Makefile.config https://gist.github.com/fallthrough/a2fbfa28cd48e03c9c2c/raw/2fd9f9570028dac87fd50b6dd37124d915c8b441/Makefile.config
make -j 8 distribute
sudo cp distribute/bin/* /usr/local/bin/
sudo cp -r distribute/include/caffe /usr/local/include/
sudo cp distribute/lib/* /usr/local/lib/
sudo cp -r distribute/python/caffe /usr/local/lib/python2.7/dist-packages/
sudo rm -rf build .build_release
sudo ldconfig

Makefile.config

## 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 := open
# 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

# 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_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

# 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

# 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 ?= @