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NGC (Nvidia GPU Cloud)

Link to section 'What is NGC?' of 'NGC (Nvidia GPU Cloud)' What is NGC?

Nvidia GPU cloud (NGC) is a GPU-accelerated cloud platform optimized for deep learning and scientific computing. NGC offers a comprehensive catalogue of GPU-accelerated containers, so the application runs quickly and reliably on the high performance computing environment. NGC was deployed to extend the cluster capabilities and to enable powerful software and deliver the fastest results. By utilizing Singularity and NGC, users can focus on building lean models, producing optimal solutions and gathering faster insights. For more information, please visit https://www.nvidia.com/en-us/gpu-cloud and NGC software catalog.

Link to section 'Getting Started' of 'NGC (Nvidia GPU Cloud)' Getting Started

Users can download containers from the NGC software catalog and run them directly using Singularity instructions from the corresponding container’s catalog page.

In addition, a subset of pre-downloaded NGC containers wrapped into convenient software modules are provided. These modules wrap underlying complexity and provide the same commands that are expected from non-containerized versions of each application.

On Scholar, type the command below to see the lists of NGC containers we deployed.

$ module load ngc 
$ module avail 

Link to section 'Example' of 'NGC (Nvidia GPU Cloud)' Example

This example demonstrates how to run LAMMPS with NGC modules.

First, let's prepare the run folder and download the input file for the example we are going to run.

$ cd $CLUSTER_SCRATCH 
$ mkdir -p lammps_ngc 
$ cd lammps_ngc 
$ wget https://lammps.sandia.gov/inputs/in.lj.txt

Then ssh to gpu and load cuda, ngc and lammps modules

$ ssh gpu.scholar.rcac.purdue.edu 
$ module load cuda 
$ module load ngc 
$ module load lammps/29Oct2020 

Finally we can set variables and start running lammps.

$ gpu_count=1 
$ input=in.lj.txt 
$ mpirun -n ${gpu_count} lmp -k on g ${gpu_count} -sf kk -pk kokkos cuda/aware on neigh full comm device binsize 2.8 -var x 8 -var y 4 -var z 8 -in ${input} 

For more information, see each application’s NGC catalog page . For applications deployed as modules, see module help command for direct link to the relevant page (e.g. module help lammps/29Oct2020 in the above example).

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