Install Yambo on Ubuntu/LinuxMint with NVfortran compiler: Difference between revisions
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The NVIDIA compiler are freely available on Linux machines. | The NVIDIA compiler are freely available on Linux machines. | ||
You can download Fortran,C, C++ compiler and debugger from: | You can download Fortran,C, C++ compiler and debugger from: | ||
[https://developer.nvidia.com/hpc-sdk-downloads NVIDIA HPC Software Development Kit (SDK) ] <br> | |||
[https://developer.nvidia.com/hpc-sdk 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-24-7 | |||
Once you downloaded and installed the NVIDIA compiler do not forget to set the correct PATH and LD_LIBRARY_PATH variables.<br> | Once you downloaded and installed the NVIDIA compiler do not forget to set the correct PATH and LD_LIBRARY_PATH variables.<br> | ||
If you want to use NVIDIA compiler in parallel you need to recompile [https://www.open-mpi.org/ openmpi] or [https://www.mpich.org/ mpich] with this compiler. | <!-- If you want to use NVIDIA compiler in parallel you need to recompile [https://www.open-mpi.org/ openmpi] or [https://www.mpich.org/ mpich] with this compiler. --> | ||
Then you can configure Yambo with the command: | Then you can configure Yambo with the command: | ||
| Line 14: | Line 18: | ||
'''Configure NVfortran with a CUDA graphic card''' | '''Configure NVfortran with a CUDA graphic card''' | ||
If you have an installed CUDA GPU on your machine you can compile Yambo to use it, by adding the flag ''--enable-cuda="cuda-version,card-version" | If you have an installed CUDA GPU on your machine you can compile Yambo to use it, by adding the flag | ||
<span style="color:#0000FF">''--enable-cuda="cuda-version,card-version"</span> | |||
with the version of your NVIDIA SDK. | * <span>''cuda-version''</span> is the version of your cuda libraries, just look in the folder ''/opt/nvidia/hpc_sdk/Linux_x86_64/'' and you will find a folder with the version of your NVIDIA SDK. | ||
* <span>''card-version''</span> refers to the compute capabilities of your card. <span>''ccXY''</span> means <span>''compute capability X.Y''</span> just have a look to the wiki webpage to see the compatibility of your card: [https://en.wikipedia.org/wiki/CUDA#GPUs_supported GPUs supported].<br> | |||
'''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: [https://www.nvidia.com/en-us/on-demand/session/gtcspring21-e32448/ Materials Design Toward the Exascale: Porting Electronic Structure Community Codes to GPUs] | |||
<span style="color:#ff0000"> | <span style="color:#ff0000">Note 1</span>: cc20 and cc30 are not support anymore in the last version of the nvidia compiler<br> | ||
<span style="color:#ff0000">Note 2</span>: if you want to use a CUDA graphic card you need to compile openmpi or mpich with the cuda support | |||
Latest revision as of 17:16, 4 November 2024
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-24-7
Once you downloaded and installed the NVIDIA compiler do not forget to set the correct PATH and LD_LIBRARY_PATH variables.
Then you can configure Yambo with the command:
./configure FC=nvfortran F77=nvfortran CC=nvc CPP="gcc -E -P" FPP="gfortran -E -P -cpp" \ --enable-open-mp --enable-par-linalg --enable-hdf5-par-io --enable-slepc-linalg
Configure NVfortran with a CUDA graphic card
If you have an installed CUDA GPU on your machine you can compile Yambo to use it, by adding the flag
--enable-cuda="cuda-version,card-version"
- cuda-version is the version of your cuda libraries, just look in the folder /opt/nvidia/hpc_sdk/Linux_x86_64/ and you will find a folder with the version of your NVIDIA SDK.
- card-version refers to the compute capabilities of your card. ccXY means compute capability X.Y just have a look to the wiki webpage to see the compatibility of your card: GPUs supported.
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
Note 1: cc20 and cc30 are not support anymore in the last version of the nvidia compiler
Note 2: if you want to use a CUDA graphic card you need to compile openmpi or mpich with the cuda support