SMU’s VPN is required to remotely access the Server. 

CPU: 20 core Arm, 10 Cortex-X925 + 10 Cortex-A725 Arm

GPU: NVIDIA Blackwell Architecture

RAM: 128 GB LPDDR5x, coherent unified system memory

SSH:

login: username@dgx.qtinslab.com

Disk/Volume

Home directories: 3.7 TB, NVMe SSD, / 'root'

SLURM

Job submission: sbatch run.shell

#!/bin/bash

#SBATCH --job-name=test_two_gpus

#SBATCH --output=test_two_gpus_%j.out

#SBATCH --error=test_two_gpus_%j.err

#SBATCH --partition=main

##SBATCH --gres=gpu:1

#SBATCH --cpus-per-task=8

#SBATCH --mem=32G

#SBATCH --time=01:00:00

echo "Running on host: $(hostname)"

echo "GPUs allocated:"

nvidia-smi

# Activate your virtual environment

source /opt/conda/etc/profile.d/conda.sh

#conda activate torch_env_3.12.4

conda activate tf_env

python test_gpu.py

Documentations: Slurm Workload Manager - Quick Start User Guide