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

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 

Once you downloaded and installed the NVIDIA compiler do not forget to set the correct PATH and LD_LIBRARY_PATH variables.
In order to to so you can execute the following lines in the shell:

NVARCH=`uname -s`_`uname -m`; export NVARCH
NVCOMPILERS=/opt/nvidia/hpc_sdk; export NVCOMPILERS
MANPATH=$MANPATH:$NVCOMPILERS/$NVARCH/25.1/compilers/man; export MANPATH
PATH=$NVCOMPILERS/$NVARCH/25.1/compilers/bin:$PATH; export PATH

Important: Do not include in the path the parallel compilers provided by NVIDIA they are bugged, recompiler OpenMPI as explained below.

Configure the parallel environment

Download OpenMPI version 4.1.7: openMPI 4.1.7 (version 5.0 has problems with NVfortran) Then configure it with the command:

./configure --prefix=somewhere CC=nvc CXX=nvc++ FC=nvfortran CFLAGS=-fPIC CXXFLAGS=-fPIC FCFLAGS=-fPIC FCFLAGS="-Mstandard -fPIC" CFLAGS=-fPIC CXXFLAGS=-fPIC

and compile it. If you have an NVIDIA card you can dd the cuda support to openMPI adding the flag --with-cuda=. See configure help for more info.

Configure Yambo with NVfortran and openMPI

Then you can configure Yambo with the command:

./configure MPIFC=mpif90 FC=nvfortran F77=nvfortran CPP="cpp -E"  FPP="nvfortran -Mpreprocess -E"  PFC=mpif90 F90SUFFIX=".f90" \
--enable-memory-profile  --enable-open-mp --enable-par-linalg  --enable-hdf5-par-io  \
--with-scalapack-libs=mkl --with-blacs-libs=mkl --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 location

of the cuda libraries, 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 greater or equal to what you set in your cuda-version in the configure. In this case we are running with driver 560, which supports up to cuda version 12.6

More info on Yambo on NVIDIA graphic cards can be found here: Materials Design Toward the Exascale: Porting Electronic Structure Community Codes to GPUs