# start BCE-2015-fall from AWS console on a g2.2xlarge
# $0.65/hour; 4 Gb video RAM, 1536 CUDA cores

# make sure to increase space for home directory by requesting more when start instance, e.g. 30 Gb

# set variable holding IP address
# export ip=52-32-169-154

# ssh to the Amazon instance
# ssh -i ~/.ssh/ec2_rsa ubuntu@ec2-${ip}.us-west-2.compute.amazonaws.com

sudo su

# install CUDA
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1504/x86_64/cuda-repo-ubuntu1504_7.5-18_amd64.deb
dpkg -i cuda-repo-ubuntu1504_7.5-18_amd64.deb

apt-get update
date >> /tmp/date
apt-get install -y cuda # a bit less than 10 mins
date >> /tmp/date

rm -rf cuda-repo-ubuntu1504_7.5-18_amd64.deb


# set up some utilities for monitoring the GPU
echo "" >> ~ubuntu/.bashrc
echo "export PATH=${PATH}:/usr/local/cuda/bin" >> ~ubuntu/.bashrc
echo "" >> ~ubuntu/.bashrc
echo "alias gtop=\"nvidia-smi -q -d UTILIZATION -l 1\"" >> ~ubuntu/.bashrc
echo "" >> ~ubuntu/.bashrc
echo "alias gmem=\"nvidia-smi -q -d MEMORY -l 1\"" >> ~ubuntu/.bashrc

# set up access to CUDA shared libraries
echo "/usr/local/cuda/lib64" >> /etc/ld.so.conf.d/cuda.conf
ldconfig

exit # back to ubuntu user

# reboot the instance

gtop

# gtop result without reboot will error:
#modprobe: ERROR: could not insert 'nvidia_352': No such device
#NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver. Make sure that the latest NVIDIA driver is installed and running. 

# create deviceQuery executable
sudo /usr/local/cuda/bin/nvcc /usr/local/cuda/samples/1_Utilities/deviceQuery/deviceQuery.cpp -I/usr/local/cuda/include -I/usr/local/cuda/samples/common/inc -o /usr/local/cuda/bin/deviceQuery

deviceQuery

# install PyCUDA
pip install pycuda

# install RCUDA
sudo su

cd /tmp
git clone https://github.com/duncantl/RCUDA
git clone https://github.com/omegahat/RAutoGenRunTime

cd RCUDA/src
ln -s ../../RAutoGenRunTime/src/RConverters.c .
ln -s ../../RAutoGenRunTime/inst/include/RConverters.h .
ln -s ../../RAutoGenRunTime/inst/include/RError.h .

cd ../..

Rscript -e "install.packages('bitops', repos = 'https://cran.cnr.berkeley.edu')"

R CMD build RCUDA
R CMD build RAutoGenRunTime
R CMD INSTALL RAutoGenRunTime_0.3-0.tar.gz 
R CMD INSTALL RCUDA_0.4-0.tar.gz 

# install MAGMA
export PATH=${PATH}:/usr/local/cuda/bin

MAGMA_VERSION=1.7.0
cd /usr/local
mkdir magma-${MAGMA_VERSION}
ln -s magma-${MAGMA_VERSION} magma
cd /usr/src
mkdir magma-${MAGMA_VERSION}
ln -s magma-${MAGMA_VERSION} magma
cd magma
wget http://icl.cs.utk.edu/projectsfiles/magma/downloads/magma-${MAGMA_VERSION}.tar.gz
tar -xvzf magma-${MAGMA_VERSION}.tar.gz
cd magma-${MAGMA_VERSION}
# note I added -fPIC per the magma README to enable creation of a shared object
cp make.inc.openblas make.inc
sed -i 's/-lopenblas/-llapack -lblas -lstdc++ -lm -lgfortran/' make.inc
sed -i 's/#GPU_TARGET.*/GPU_TARGET = Kepler/' make.inc
sed -i 's/.*(CUDADIR)\/lib64/LIBDIR\t\= -L$(CUDADIR)\/lib64/' make.inc
sed -i 's/.*OPENBLASDIR.*//' make.inc
sed -i 's/.*make.check-openblas.*//' make.inc
# make NVCCFLAGS look like:
# NVCCFLAGS = -O3         -DADD_       -Xcompiler "-fno-strict-aliasing $(FPIC)"

export CUDADIR=/usr/local/cuda
make shared 2>&1 | tee ../make.shared.log
make test 2>&1 | tee ../make.test.log
make install prefix=/usr/local/magma 2>&1 | tee ../make.install.log

cd /usr/local/magma
chmod ugo+r include/*

echo "/usr/local/magma/lib" >> /etc/ld.so.conf.d/SITE-magma.conf
ldconfig


#### Create image ##########################

# 1) now save the image in us-west-2 via point and click on VM page under Actions
# 2) make it public