Campus Research Computing Options


Research computing is complex and multi-faceted, incorporating a variety of resources and models. These can include high-performance computing, stand-alone computation systems, cloud computing, and more. Our goal for this article is to show you what is available and hopefully assist in assessing what solution(s) will enable your work. 

As a member of the Grainger College of Engineering, you will have access to our multi-year investment in the Illinois Campus Cluster Program free of cost. This high-performance computing (HPC) resource currently has 10 compute nodes and 46 NVidia A10 GPUs, and is intended for short-term or exploratory work and can be used for both research and instructional purposes. Another resource at Illinois is the Delta computing environment which has more than 800 GPUs available as part of the ACCESS network of computational systems funded and allocated through the NSF. Additionally, there is a 4,300 core high-throughput computing (HTC) condor cluster available for use. Each of these resources can be leveraged at no or low cost, but for faculty with more intensive compute needs Engineering IT can help design or connect you to a solution that more directly meets your specific project needs. A chart comparing the computational resources most commonly used by Engineering researchers can be found below.

Top Computational FAQs

Are you working on Machine Learning or Artificial Intelligence simulations?
If you are, you likely already know that you'll likely require a system with powerful graphics cards, what you may not know is that there are several computational resources available that you can leverage instead of purchasing your own system.

Are the simulations or tasks you running easy for a regular computer to complete but needs to be ran hundreds to hundreds of thousands of times?
This is known as a "perfectly parallel" workload and is generally a good candidate for High-Throughput Computing solutions. 

What software does your project require to run your simulations or tasks?
Many computational resources have certain software packages natively available, some have the ability to add additional software by request or onto your own profile. 


Additional Questions

There are other questions to consider when determining the appropriate computational resource for your project, you can find some of them below.
If you would like to meet with someone to discuss your needs please email the Research Technology Facilitator, Ethan Conner ( 

  • Are you working with sensitive information, whether it be the input or output data, or the code that you are running?
  • Will your simulations be leveraging a Message Passing Interface (MPI)?
  • Do you require a computational resource that does not have a wall time (termination of job if not completed in X time)?
  • How versed are your project members in Linux distributions or command line?


Computing Resources (At-a-Glance)

A full-sized version of this matrix can be found here.

  Illinois Campus Cluster Delta Nightingale Radiant HOLL-I HAL Innovative Systems Lab HT Condor Pilot ACCESS AWS AZURE
TYPE OF RESOURCE High-Performance Computing High-Performance Computing Secure High-Performance Computing High-Performance Computing AI High-Performance Computing High-Performance AI/GPU Computing EXPERIMENTAL High-Throughput Computing Varied Research Computation Services Varied Varied
WEBSITE Campus Cluster Delta | NCSA Nightingale | NCSA Radiant | NCSA HOLL-I | NCSA HAL Cluster | NCSA Wiki Innovative Systems Lab HTC Wiki ACCESS AWS at Illinois Azure at Illinois
COST OF USE Varies by selected investment option.
Engineering users can use a college-level investment at no cost. 
FREE (with approved allocation) Fees and Services Rates HOLL-I | NCSA FREE (with approved allocation) FREE (with approved allocation)  FREE  FREE (with approved allocation) Varies by selected options Varies by selected options
HARDWARE ICCP Node Information System Architecture System Architecture Technical Specifications HOLL-I | NCSA  HAL Cluster ISL Information Retired Campus Cluster Nodes (various configurations) Varies by resource N/A N/A
PRIMARY USE CASES The Illinois Campus Cluster provides access to computing and data storage resources and frees you from the hassle of administering your own compute cluster. Delta is a GPU based compute platform for Artificial Intelligence and Machine Learning, Simulation, and Data Science Nightingale is a high-performance compute cluster with storage for researchers to interact with protected data and perform analysis. (HIPAA, ePHI, CUI, FERPA approved) Radiant provides researchers a flexible, elastic, and scalable computing solution, using cloud-like virtualization, while remaining on-site at NCSA. HOLL-I (Highly Optimized Logical Learning Instrument) is a new service at NCSA that offers public access to an extreme scale machine-learning capability through a Cerebras CS-2 WSE.  The Hardware-Accelerated Learning (HAL) cluster was designed to speed up deep learning research. It integrates the most recent advances in computing, storage and interconnectivity technologies to create a purpose-built shared-use system.  Cutting-edge computing environments for experimentation and evaluation Jobs that are more ideally suited to a High Throughput (loosely coupled) environment The available resources in ACCESS have different uses, a list of resources and subsequent information can be found here. A variety of use cases can be found here A variety of use cases can be found here
HOW TO GET STARTED Engineering users can take advantage of a college-level investment at no cost. Email Allocations managed through ACCESS Accessing the System Requesting Resources or Starting a project - Email requesting for access to HOLL-I  New User Guide for HAL System Contact 
Vlad Kindratenko
Request Access ACCESS Allocations: Get started Request an AWS Account Request an Azure Account
USER GUIDES / ONLINE SUPPORT Campus Cluster User Guide Delta User Guide Nightingale User Guide User Documentation Directory User Documentation 
(Requires HOLL-I account/access)
HAL cluster Experimental systems, so very little support available Minimal on-campus support,  but user community has a   wealth of information. ACCESS Knowledge Base Getting started with AWS Azure Tutorials from Microsoft
SOFTWARE PACKAGES a variety of core software and libraries available  Complete List Here Software Software Openstack Components

CSoft 1.5 for CS-2 WSE (more information in User Documentation)

Software for HAL

Several technologies including test openstack, gpu, Kubernetes, etc

HT Condor pilot shares many software packages with the Engineering Linux Environment Varies by resource, a list and subsequent info on resource providers can be found here. AWS Products (external site) Azure Products (external site)
DATA STORAGE OPTIONS 7GB Quota (additional storage available for purchase) File Systems Fees and Services: Storage Rates 1TB per project on TAIGA as part of access, additional storage available at standard TAIGA rates. Access to any existing TAIGA storage  N/A Varies on project scope usually 1-2TB per project  10GB initial quota Varies by resource Scalable to the project via EC2 and other AWS offerings Scalable to the project

If none of the computing resources listed above meet your needs, Engineering IT is available to help create and support a solution tailored to your project’s computing requirements. Email to get started.


Grainger College of Engineering's Computational Resources

Illinois Campus Cluster Program

The Grainger College of Engineering (GCoE) has an investment into the Illinois Campus Cluster Program (ICCP); this resource is available to faculty, staff, and students in the GCoE at no cost for both research and instructional purposes. (There are currently a total of 10 InfiniBand interconnected compute nodes providing 832 CPU cores and 46 A10 GPUs).

  • 10 InfiniBand interconnected compute nodes providing 832 CPU cores and 46 A10 GPUs
       - 5 GPU nodes, 1x AMD EPYC 7763 (64-core), 320 cores total, 2560GB RAM (512GB ea.), 40x A10 GPUs (8 ea.)
       - 3 CPU nodes, 2x AMD EPYC 7713 (64-core), 384 cores total, 3TB RAM (1TB ea)*
       - 2 GPU nodes, 2x Intel Xeon 8358 (32-core), 128 cores total, 512GB RAM (256GB ea), 6x A10 GPUs (3ea.)* 

     Note: the resources marked with an asterisk (*) are assigned to our dedicated queue for instructional use

29TB of shared storage

High-Throughput Condor Pilot

Additionally, GCoE has a 4,300-core High-Throughput Computing resource available based on HT Condor. Both of these resources can be used at zero cost to anyone affiliated with the college.


Grant and Proposal Support

In order to cite the Illinois Campus Cluster Program in your work, or to prepare a budget for your grant proposal, please take advantage of the prepared documentation and sample budget template information here:


Training Resources