Install Yambo on Ubuntu/LinuxMint with NVfortran compiler
The NVIDIA compiler are freely available on Linux machines.
You can download Fortran,C, C++ compiler and debugger from:
NVIDIA HPC Software Development Kit (SDK)
On Ubuntu, it can be easely installed via the following procedure
sudo apt-get update -y && sudo apt-get upgrade -y sudo apt-get install -y build-essential automake autoconf libtool zlib1g-dev curl gpg wget git tar cmake curl https://developer.download.nvidia.com/hpc-sdk/ubuntu/DEB-GPG-KEY-NVIDIA-HPC-SDK | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-hpcsdk-archive-keyring.gpg echo 'deb [signed-by=/usr/share/keyrings/nvidia-hpcsdk-archive-keyring.gpg] https://developer.download.nvidia.com/hpc-sdk/ubuntu/amd64 /' | sudo tee /etc/apt/sources.list.d/nvhpc.list sudo apt-get update -y && sudo apt-get install -y nvhpc-25-1
Setup NVIDIA compilers
Once you downloaded and installed the NVIDIA SDK it is suggested avoiding manually setting environment variables for compilers and MPI wrappers. The safest approach is to use the module files provided by Nvidia, located at: `/opt/nvidia/hpc_sdk/modulefiles`
Before using module files, you need to install the module management tool:
sudo apt-get install environment-modules echo "source /etc/profile.d/modules.sh" >> ~/.bashrc echo "module use /opt/nvidia/hpc_sdk/modulefiles" >> ~/.bashrc source ~/.bashrc
The commands above only need to be used the first time. Now, you can load the Nvidia SDK module, which will correctly set up all environment variables for both compilers and MPI:
module load nvhpc/25.1
Configure Yambo with NVfortran and openMPI
Then you can configure Yambo with the command:
./configure MPIFC=mpif90 MPICC=mpicc FC=nvfortran F77=nvfortran CPP="cpp -E" FPP="nvfortran -Mpreprocess -E" F90SUFFIX=".f90" \ --enable-memory-profile --enable-open-mp --enable-par-linalg --enable-hdf5-par-io --enable-slepc-linalg
If you have an installed CUDA GPU on your machine you can compile Yambo to use it, by adding the flag
--enable-cuda-fortran
and then specify your GPU architecture and the CUDA runtime version, look at configure help for more info.
Check that your Nvidia graphic card is properly installed
To be sure that the code will run fine on your GPU card, you need the proper driver installed on your machine. If you have the nvidia drivers, just run
$nvidia-smi Mon Sep 9 16:20:02 2024 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 560.35.03 Driver Version: 560.35.03 CUDA Version: 12.6 | |-----------------------------------------+------------------------+----------------------+ | GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 NVIDIA GeForce GTX 1650 Off | 00000000:01:00.0 On | N/A | | 20% 39C P8 8W / 75W | 280MiB / 4096MiB | 0% Default | | | | N/A | +-----------------------------------------+------------------------+----------------------+
CUDA Version: V.S should be lower or equal to what you set in your cuda-runtime in the configure. In this case we are running with driver 560, which supports cuda version 12.6 or newer via the CUDA Forward Compatibility Package (see https://docs.nvidia.com/deploy/cuda-compatibility/).
More info on Yambo on NVIDIA graphic cards can be found here: Materials Design Toward the Exascale: Porting Electronic Structure Community Codes to GPUs