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"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." (

paraphrazed from your

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: 

Volodymyr

V. Kindratenko,

Dawei

D. Mu,

Yan

Y. Zhan,

John

J. Maloney,

Sayed Hadi

S. Hashemi,

Benjamin

B. Rabe,

Ke

K. Xu,

Roy

R. Campbell,

Jian

J. Peng, and

William

W. Gropp

. 2020

. HAL: Computer System for Scalable Deep Learning.

InPractice

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

Software

Documentation

Science on HAL

Software for HAL


To request access: fill out this form. Make sure to follow the link on in the application confirmation page 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:8888//

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-login2.ncsa.illinois.edu 

To submit interactive job:

Code Block
languagebash
swrun -p gpux1

To submit a batch job:

Code Block
swbatch run_script.swb  

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 wmlce

To see CLI scheduler status:

Code Block
swqueue



Main -> Systems -> HAL

Contact us

Request access to this system: Application

Contact ISL staff: Email Address

Visit: NCSA, room 3050E


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