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In publications and presentations that use results obtained on this system, please include the following acknowledgement: “This work utilizes resources supported by the National Science Foundation’s Major Research Instrumentation program, grant #1725729, as well as the University of Illinois at Urbana-Champaign”.

System Description

Host name:



  • CentOS 7RHEL 8
  • CUDA 11
  • NCCL
  • cuDNN
  • TensorRT
  • 12

User Guide

To request an account: email


Use /home/<username> for basic stuff only, do not put any code/data here as the /home partition is very small. Quota: 50GB per User

Use /projects file system for all your data/code. Create a subfolder in this partition for your username and keep your stuff there. Quota: 2TB/10 million inodes per User

Use /scratch file system for ephemeral/transient data that is created during job runs that doesn't need to be kept long term. (And do not forget to remove it after the job is done and you no longer need it!)

To access the system, submit jobs, etc.: Access HAL-DGX and OVERDRIVE servers through HAL-LOGIN3 node

To compile CUDA applications, first enable devtoolset 9

Code Block
scl enable devtoolset-9 bash

CUDA tools are already in the path, just use nvcc to compile.

To work with Python

, create

, there are several versions installed, from 2.7 to 3.9. Create and enable virtual environment first, e.g., to use 3.8:

Code Block
python3.8 -m venv python3python38-virtualenv
source python3python38-virtualenv/bin/activate

You can use pip to install python packages within this environment.

To start a Jupyter notebook on hal-dgx

  • on hal-dgx:
Code Block
# source python3your python environment, e.g., 3.8
source python38-virtualenv/bin/activate
pip install jupyter # this needs to be done only once
jupyter notebook --port=9999 # this will start the jupyter server on port 9999. Pick a different port if it fails to start
  • on your own computer:
Code Block
# This opens a connection to the Jupyter server, and 
# forwards any connection to port 8888 on the local machine to port 9999 on
ssh -L 8888:localhost:9999 <userid>
  • Finally, on your own computer, open web browser and point it to the address you see after running 'jupyter notebook' on hal-dgx, something like http://localhost:8888/?token=...
    • Make sure to replace the port in the URL with the port on your localhost

Main -> Systems -> DGX A100

Contact us

Request access to ISL resources: Application

Contact ISL staff: Email Address

Visit: NCSA, room 3050E