Empire AI

Empire AI provides high-performance compute resources to eligible PIs across a consortium of New York State research institutions to advance safe, equitable, and responsible AI research for the public good. 

Related Links

Empire AI
Empire AI Knowledge Base (wiki for users)

Executive Order 62: Empire AI and New York's Data Center Moratorium

On July 14, 2026, Governor Hochul signed Executive Order No. 62, pausing discretionary state permitting for new hyperscale data centers while New York develops updated environmental and grid standards. Empire AI is exempt from this Order, which excludes facilities primarily used for research, including Empire AI and academic research at accredited colleges and universities.

September 2026: Columbia launches monthly Empire AI User Sessions

These webinars provide a Columbia-specific space for users to ask questions and work through setup, job submission, and general Empire AI usage. Sessions will be announced to all Empire AI users via email, with Zoom links provided and recordings available in the RCS Video Library.

Title slide reading "Columbia Empire AI Monthly User SessionResource overview, updates, and open Q&A for the Columbia Empire AI User Community"

Examples of Existing Columbia Project Categories on Alpha

  •  Foundation Models and Generative AI
  • AI for Scientific Discovery and Simulation
  • Natural Language Processing and Understanding
  • Machine Learning Methodology and Applications
  • And more…

Timeline

Empire AI was launched in April 2024, marking the beginning of a multi-phase initiative to expand AI research capacity across New York State. By October 2024, the Alpha system became operational at the University at Buffalo, followed by the Beta system award and the conceptual design of the Gamma system in January 2025. 

The Beta system is scheduled to come online end of May 2026 and construction of the Gamma facility will begin in early 2027. The Gamma facility is expected to open in Mid-late 2027, with the full Gamma system becoming operational in the first half of 2028.

Data Compliance 

Empire AI is not currently certified to hold/process sensitive data (RHI, PII, PHI-related clinical data). Please refer to the University's Data Classification Policy if you are not sure your data's classification, and ensure that you do not use sensitive data on the system. 

Alpha Hardware Specifications

The Alpha system initially consisted of 13 HGX nodes with 8 H100 80GB GPUs per node and 4 PB of storage across DDN and VAST. Alpha was recently upgraded to Alpha++ over Fall 2025, with now 24 HGX nodes: 

24 HGX Nodes

  • Nodes alphagpu01 - alphagpu18
    • 8 H100 80GB GPUs per node
  • Nodes alphagpu19 - alphagpu24

    • 8 H200 80GB GPUs per node

  • 10 400Gb/s ConnectX-7 NIC Cards (8 for IB and 2 for Ethernet)
  • 30TB NVMe caching space
  • 2TB of system memory
  • x86 processor
  • Storage:
    • 2PB of DDN Storage
    • 2PB of VAST (all flash)


Research: There are currently over 120 active projects and 320 users across all the institutions on Empire AI.

Beta Hardware Specifications

Compute: NVIDIA DGX GB200 SuperPOD

  • 4 racks NVL72 with 288 B200 GPUs for AI Applications
  • 60 Grace-Grace Superchip nodes for data processing and general HPC use

Storage: ~10 PB DDN; ~20 PB VAST all flash Software: NVIDIA AI Enterprise Software

Institutional Allocation & Service Units 

Empire AI provides a range of compute nodes and storage options, each with varying performance levels and costs. To ensure consistency in measuring and managing usage, all resources are expressed in a unified metric known as Service Units (SUs). 

Alpha and Beta will deliver 6.3M SUs per year with each institutional allocation at 700,000 SUs per year. Each approved Columbia project is allowed to request an initial allocation of up to 2,000 SUs. Additional requests for SUs can be made throughout the year and will be reviewed on a case by case basis.

With the Beta phase, all computer resources are assigned a value in Service Units, for example:

  • 1 Alpha GPU hour = 1 SU
  • 1 Beta GPU hour = 2 SU
  • 1 Grace-Grace node hour = 0.5 SU
  • 1 TB.month = 8.333 SU up to 100 TB, data over 100 TB will be free but allocated and managed separately
  • Priority queue access 2x the above
  • Shared resource access 0.5x the above
  • These above conversion factors are termed multipliers.
  • Cost of a job in SUs = duration * amount of resources * multiplier


Cost Per Service Unit

For Empire AI, 1 SU will equate to $0.50. For Columbia users, the University will be subsidizing 50% of the cost, therefore $0.25/SU. Individual Schools and Departments may provide additional subsidies to further reduce the effective SU cost for their users.

Eligibility

Only those who hold a full-time appointment in a PI-eligible position at Columbia University may submit project proposals for Empire AI. For more clarification on PI eligibility please see: https://research.columbia.edu/pi-eligibility-sponsored-projects

Reference Documentation

The following guides are also available to help you get started:

Grant Proposal Language

In your grant proposals, in the following sections (or their equivalent), please use the language provided below.

Budget Justification:

The cost of compute and memory resources on Empire AI are calculated based on the University’s established costing method. A service unit is used as the unit of measure to charge for compute resources across the users of Empire AI.

Facilities Section:

Columbia University provides access to compute resources through Empire AI. Empire AI is a consortium of nine New York State institutions that, with support from New York State, oversees a shared computing facility to promote responsible research and development, including the advancement of the ethical and public-interest uses of artificial intelligence (AI) and high-performance computing (HPC) technologies in New York.

Note:  If you need to include additional technical details on Empire AI's computational, storage, and networking capabilities, please see this website.  Please contact Sharon Sputz ([email protected]) for any questions.
 

How To Acknowledge Use of Empire AI 

To cite the use of Empire AI in your papers, please add this sentence in your acknowledgements:  
"We gratefully acknowledge use of the research computing resources of the Empire AI Consortium, Inc, with support from the State of New York, the Simons Foundation, and the Secunda Family Foundation." 
 

Contact Us

Please send any inquiries to [email protected]. A ServiceNow ticket will be generated and a member of the Columbia Empire AI Support Team will be able to assist further.

Frequently Asked Questions

A Service Unit (SU) is the standard unit of accounting that Empire AI uses to measure and manage resource usage across its systems. 

Because Empire AI includes different types of compute nodes (Alpha GPUs, Beta GPUs, Grace-Grace nodes) and storage, each with different performance characteristics and costs, the SU provides a common currency that allows all usage to be compared fairly, regardless of the underlying hardware or service.

Projects will not be charged for more than their allocation. However, any projects that have exceeded their SU allocations will only have access to the free, low-priority, preemptible burst queue (that is otherwise inaccessible) and will be requested to reduce their storage footprint as described in the Empire AI terms and conditions. This policy provides a smooth end to projects, helps ensure full system utilization, and encourages projects to promptly use allocations. Users with no allocation will be transitioned off the system after some period of time, again as described in the terms and conditions.

To request more SUs, please submit a new iLab Empire AI request.

  1. Log into iLab via the CUIT Research Services iLab link using your UNI credentials at https://cumc.corefacilities.org/account/login.
  2. Expand the Empire AI dropdown at the bottom of the page and click the Request Service button.
  3. Enter the desired amount of Service Units (SUs) in the Quantity field. The total price will update automatically.
  4. Scroll down to the Payment Information section and select the chartstring(s) to use for payment.

    You can also use the attached guide on how to submit the request. 

Please email [email protected] (this will create a ticket that will be assigned to Columbia's iLab administrator) and provide the following information: 

  • PI’s name
  • PI's email address
  • Full unrestricted chartstring: Project|Activity|Segment|Department|Initiative|
  • Optional: UNIs of others in the lab that need access to the project (or the PI can do this later via the "Membership Requests & Chart Strings" tab in iLab)

Check our Empire AI Confluence Knowledge Base for more information on data transfers on Empire AI.

Currently, Beta is not certified to handle sensitive or HIPAA data, however there are plans to handle sensitive data and anticipate compliance by late 2026/early 2027 for a subset of the system.

As feasible and appropriate, please both cite the article below and include the acknowledgement.

1. Please cite the following article to automate tracking of papers

Stacie Bloom, Joshua C. Brumberg, Ian Fisk, Robert J. Harrison, Robert Hull, Melur Ramasubramanian, Krystyn Van Vliet, and Jeannette Wing. 2025. Empire AI: A new model for provisioning AI and HPC for academic research in the public good. In Practice and Experience in Advanced Research Computing (PEARC ’25), July 20–24, 2025, Columbus, OH, USA. ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3708035.3736070

or in BibTeX format:

@inproceedings{Bloom2025EmpireAI,

author    = {Stacie Bloom and Joshua C. Brumberg and Ian Fisk and Robert J. Harrison and Robert Hull and Melur Ramasubramanian and Krystyn Van Vliet and Jeannette Wing},

title     = {Empire {AI}: A new model for provisioning {AI} and {HPC} for academic research in the public good},

booktitle = {Practice and Experience in Advanced Research Computing ({PEARC} '25)},

pages     = {4},

year      = {2025},

month     = {July},

address   = {Columbus, OH, USA},

publisher = {ACM},

location  = {New York, NY, USA},

doi       = {10.1145/3708035.3736070},

url       = {https://doi.org/10.1145/3708035.3736070}

}

2. Please include this acknowledgement

We gratefully acknowledge use of the research computing resources of the Empire AI Consortium, Inc, with support from Empire State Development of the State of New York, the Simons Foundation, and the Secunda Family Foundation.