Installing GROMACS on Ubuntu with CUDA GPU Support

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6 mins read
Install gromacs with gpu acceleration

GROMACS [1] is one of the most popular software in bioinformatics for molecular dynamic (MD) studies of macromolecules. We have provided different tutorials regarding MD simulation using GROMACS including its installation on Ubuntu. In this article, we will install GROMACS with GPU acceleration.

For detailed instructions, read our previous article. If you want to install without GPU support, you can simply follow the steps mentioned in that article. In this tutorial, you will find some additional steps for GPU acceleration.

Getting Started

It is good practice to update your repository information and software packages before installing new programs. Open a terminal by pressing Ctrl+Alt+T and type:

$ sudo apt-get update

$ sudo apt-get upgrade

Downloading CUDA toolkit

It might be possible that you have already NVIDIA CUDA drivers installed on your system. Therefore, it’s better to first remove them and then install the latest drivers, otherwise, it will give you errors. Open a terminal and type the following commands:

$ sudo apt-get remove --purge cuda-* libcuda* nvidia*

$ sudo apt-get remove --purge cuda-drivers libcuda* cuda-runtime* cuda-8-0 cuda-demo*

$ sudo apt-get autoremove --purge nvidia* cuda-drivers libcuda* cuda-runtime* cuda-8-0 cuda-demo*

$ sudo apt-get remove --purge nvidia* cuda-drivers libcuda1-396 cuda-runtime-9-2 cuda-9.2 cuda-demo-suite-9-2 cuda

Now select the latest version of the CUDA toolkit according to your system from here. Download the local run file using the following command. The run file contains every essential component to be installed. Change to the directory where you want to download the installer.

$ cd Downloads/

$ wget https://developer.download.nvidia.com/compute/cuda/11.1.1/local_installers/cuda_11.1.1_455.32.00_linux.run

Installing CUDA toolkit

Since the CUDA toolkit is available for Ubuntu 16.04 onwards, therefore, make sure you have the compatible version of Ubuntu installed on your system. Now, copy & paste the following command to run the installer.

$ sudo sh cuda_11.1.1_455.32.00_linux.run

It will ask to create a password, enter, and confirm. It will take a few minutes to finish. After that, edit /etc/ld.so.conf file.

$ sudo gedit /etc/ld.so.conf

Now add the following path at the end of the file.

/usr/local/cuda-11.1/lib64

$ sudo ldconfig

Now install CUDA drivers. To avoid any error, don’t forget to write the last argument in the command (–override-driver-check).

$ sudo sh cuda_11.1.1_455.32.00_linux.run --silent --driver --override-driver-check

Updating NVIDIA drivers

It is necessary to update the NVIDIA drivers otherwise it will not recognize GPU during simulation even after configuration. Copy & paste the following commands.

$ sudo ubuntu-drivers autoinstall

$ sudo apt-get update

Installing prerequisites for GROMACS

  • Install openmpi from the repository using the following command:

$ sudo apt-get install libopenmpi-dev

$ sudo apt-get install openmpi-bin

$ sudo apt-get install mpi4py

If you have already installed GROMACS, then skip to the next step.

  • Get cmake before installing GROMACS. In the terminal, type:

$ sudo apt-get install -y cmake

After the installation finishes up, you can check the version of cmake by the following command:

$ cmake --version

If it displays the version, then it means everything is fine. Move on to the next step.

  • The next requirement is build-essential. To install this, type the following command in the terminal:

$ sudo apt-get install -y build-essential

  • Now, you need the FFTW3 library. Install it using the following command:

$ sudo apt-get install -y libfftw3-dev

  • Now, install Doxygen

$ sudo apt-get install -y doxygen

Downloading Regressiontests

It is better to download the regressiontests separately because most of the time it throws an error stating that “the location of the file has changed”. Copy and paste the following commands in your terminal:

$ cd Downloads/

$ wget http://gerrit.gromacs.org/download/regressiontests-2020.4.tar.gz

Now, extract the downloaded file,

$ tar xvzf regressiontests-2020.4.tar.gz

Downloading GROMACS

Download the latest release of GROMACS from here or use the following command:

$ wget ftp://ftp.gromacs.org/pub/gromacs/gromacs-2020.4.tar.gz

Installing GROMACS

First, get your pwd path using the following command:

$ pwd

Note down the displayed path, we will need it in later steps.

  • Extract the downloaded archive file. Move into the directory where you have downloaded the package. Let’s say, Downloads.

$ cd Downloads/

$ tar xvzf gromacs-2020.4.tar.gz

  • Now move inside the gromacs folder.

$ cd gromacs-2020.4/

  • Create a directory called “build-gpu” where we will keep our compiled binaries.

$ mkdir build-gpu

  • Move inside the build-gpu directory

$ cd build-gpu/

  • Now, make gromacs using cmake.

$ sudo cmake .. -DGMX_BUILD_OWN_FFTW=OFF _DREGRESSIONTEST_DOWNLOAD=OFF -DMAKE_C_COMPILER=gcc -DGMX_GPU=ON -DGMX_MPI=OFF -DREGRESSIONTEST_PATH=/your/pwd/path/here/Downloads/regressiontests-2020.4

If everything goes well, the message in your terminal will say “Generating Done. Build files written… “. If not, make sure you have replaced the pwd path in command with the path of your home directory.

  • Now, let’s check and make.

$ make check

$ sudo make install

  • Move inside the unpacked regressiontests directory and execute the following command:

$ source /usr/local/gromacs/bin/GMXRC

After that, you can check for the successful installation of GROMACS with the following command:

$ gmx pdb2gmx --version

It will display the GPU version as well.

Enjoy the speedy simulation!

Muniba is a Bioinformatician based in the South China University of Technology. She has cutting edge knowledge of bioinformatics tools, algorithms, and drug designing. When she is not reading she is found enjoying with the family. Know more about Muniba
Tariq is founder of Bioinformatics Review and a professional Software Developer at IQL Technologies. His areas of expertise include algorithm design, phylogenetics, MicroArray, Plant Systematics, and genome data analysis. If you have questions, reach out to him via his homepage.

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