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System Description

"My name is HAL. I became operational on March 25 2019 at the Innovative Systems Lab in Urbana, Illinois. My creators are putting me to the fullest possible use, which is all I think that any conscious entity can ever hope to do." (paraphrased from https://en.wikipedia.org/wiki/HAL_9000)

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”.

Also, please include the following reference in your publications: V. Kindratenko, D. Mu, Y. Zhan, J. Maloney, S. Hashemi, B. Rabe, K. Xu, R. Campbell, J. Peng, and W. Gropp. HAL: Computer System for Scalable Deep Learning. In Practice and Experience in Advanced Research Computing (PEARC ’20), July 26–30, 2020, Portland, OR, USA. ACM, New York, NY, USA, 15 pages. https://doi.org/10.1145/3311790.3396649”.

Hardware-Accelerated Learning (HAL) cluster


Info

Effective May 19, 2020, two-factor authentication via NCSA Duo is now required for SSH logins on HAL. See https://go.ncsa.illinois.edu/2fa for instructions to sign up.


Host name: hal.ncsa.illinois.edu

Hardware

GB

Software

RHEL 7
6
10
  • 11.
1
  • 2.
105
7
    • 8.
5
    • 1.
0
4
    • 8.
2
  • IBM XLC 16.1.1
  • IBM XLFORTRAN 16.1.1
  • Advance toolchain for Linux on Power 12.0
  • PowerAI 1.6.0
  • SLURM

    Documentation

    management
    Modules management

    Science on HAL

    Software for HAL


    To request access: fill out this form. Make sure to follow the link in the confirmation email to request actual system account.

    Frequently Asked Questions

    To report problems: email us

    For our new users: New User Guide for HAL System

    User group Slack space: https://join.slack.com/t/halillinoisncsa

    Real-time system status: https://hal-monitor.ncsa.illinois.edu:3000

    HAL OnDemand portal: https://hal-ondemand.ncsa.illinois.edu/

    Globus Endpoint: ncsa#hal

    Quick start guide: (for complete details see Documentation section on the left)

    To connect to the cluster:

    Code Block
    ssh 
    username@hal
    <username>@hal-login2.ncsa.illinois.edu 
    Time limits:
    • Interactive queue: 12 hours
    • Batch queue:  72 hours

    To submit interactive job:

    Code Block
    languagebash
    srun
    swrun -
    -partition=debug --pty --nodes=1 \ --ntasks-per-node=8 --gres=gpu:v100:1 \ -t 01:30:00 --wait=0 \ --export=ALL /bin/bash
    p gpux1

    To submit a batch job:

    Code Block
    sbatch
    swbatch run_script.
    sb
    swb  

    See run_script.sb for a basic example.

    To load IBM PowerAI

    Job Queue time limits:

    • "debug" queue: 4 hours
    • "gpux<n>" and "cpun<n>" queues:  24 hours

    To load IBM Watson Machine Learning Community Edition (former IBM PowerAI) module:

    Code Block
    module load 
    ibm/powerai
    wmlce

    To see CLI scheduler status:

    Code Block
    swqueue



    Main -> Systems -> HAL

    Contact us

    Request access to ISL resourcesthis system: Application

    Contact ISL staff: Email Address

    Visit: NCSA, room 3050E


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