System description
CPU - Intel(R) Core(TM) i7-7500 @2.70 GHz
GPU chip - NVIDIA GeForce 930MX
OS - Ubuntu 16.04 LTS 64 bit
Setting up the NVIDIA driver and CUDA
#Download NVIDIA-Linux-x86_64-384.111.run from http://www.nvidia.com/Download/driverResults.aspx/128737/en-us
#Download cuda_8.0.61_375.26_linux.run from https://developer.nvidia.com/cuda-80-ga2-download-archive
#Remove previous versions (if applicable to you)
sudo apt-get --purge remove nvidia-*
sudo nvidia-uninstall
#press ctrl+alt+F2 to go to a tty session and login with your username and password
sudo service lightdm stop
#Blacklist nouveau drivers
# Create a file named blacklist-nouveau.conf inside /etc/modprobe.d with the following content
blacklist nouveau
options nouveau modeset=0
#Regenerate the kernel initramfs
sudo update-initramfs -u
#Run the install script for NVIDIA driver
sudo sh NVIDIA-Linux-x86_64-384.111.run --no-opengl-files
#If --no-opengl-files is not specified above, you will run into a login loop.
#If you get the message that the script failed, choose "continue"
#If you are given the option to register the kernal module sources with DKMS, choose "Yes"
#If you are given the option to install the 32-bit compatibility libraries, choose "No"
#Run the install script for CUDA
sudo sh cuda_8.0.61_375.26_linux.run --no-opengl-libs
#If you are given the option to install the NVIDIA driver, choose "no"
#Give the preferred location for installation or accept the defaults
#Reboot the system by typing
sudo reboot
#Add the cuda-8.0/bin location to the PATH
#Add the cuda-8.0/lib64 location to the LD_LIBRARY_PATH
Installing PLUMED
#Run the following commands for needed software
sudo apt-get install git cmake gawk
sudo apt-get install libmatheval-dev
sudo apt-get install libopenmpi-dev openmpi-bin
sudo apt-get install gnuplot
sudo apt-get install python3 python3-numpy python3-scipy
#Get the location of matheval.h which will later be specified with CPPFLAGS
sudo find / -name matheval.h
#Download PLUMED from http://www.plumed.org/get-it
#Untar the file and do the installation
tar -xvzf plumed-2.4.0.tgz
cd plumed-2.4.0
sudo ./configure CPPFLAGS=-I/usr/include CC=mpicc CXX=mpicxx
make -j 4
sudo make install
GROMACS installation
#Download gromacs 5.1.4 from http://manual.gromacs.org/documentation/5.1.4/download.html
#Untar, patch with PLUMED and install
tar -xvzf gromacs-5.1.4.tar.gz
cd gromacs-5.1.4
plumed patch -p --runtime -e gromacs-5.1.4
mkdir build
cd build
#Find the location of the nvml.h file and specify the directory path under -DNVML_INCLUDE_DIR later with camke
sudo find / -name nvml.h
#Find the location of the libnvidia-ml.so file and specify the file path under -DNVML_LIBRARY later with camke
sudo find / -name libnvidia-ml.so
#Type the below command in the same line.
cmake .. -DGMX_BUILD_OWN_FFTW=on -DGMX_MPI=on -DCMAKE_C_COMPILER=mpicc -DCMAKE_CXX_COMPILER=mpicxx -DGMX_GPU=on -DNVML_INCLUDE_DIR=/usr/local/cuda-8.0/include -DNVML_LIBRARY=/usr/lib/x86_64-linux-gnu/libnvidia-ml.so
make -j 4
sudo make install
Like!! Really appreciate you sharing this blog post.Really thank you! Keep writing.
You are welcome!
Thanks designed for sharing such a good idea, paragraph is fastidious, thats why i have
read it entirely
You are welcome!
Is this valid for Debian distribution?
It worked for me on Ubuntu. It would probably work on Debian as well. I haven’t tried though.
Did you install Ubuntu VDI in your local windows operating system or did you install Ubuntu operating system separately on your hardware?
This is for a machine running on Ubuntu only.