Beta User Workshop
Virtual
Join us for an interactive workshop to learn about GP-STOR and get started as a beta user
Providing distributed, resilient storage infrastructure for data-intensive research, AI/ML workflows, scientific simulations, and collaborative discovery across the Great Plains region.
Capacity as designed. Hardware is in procurement now. See the roadmap
GP-STOR connects researchers and institutions across Missouri, Nebraska, and South Dakota to accelerate discovery through reliable, scalable, and accessible data infrastructure.
A tier for the data you keep and a tier for the data you are working on right now, reachable from the compute you already use.
14 PB of redundant Ceph object storage for data at rest, plus 384 TB of solid-state storage for AI/ML streaming, simulation output, and instrument data.
Capacity is split across the University of Missouri, the University of Nebraska, and the University of South Dakota, so one site going offline does not take your data with it.
Mounts for the OSG and the National Research Platform, Globus transfers, OSDF origins, and a web UI, so jobs and transfers run through the tools already in use.
Virtual office hours, video walkthroughs, and step-by-step guides, so a group new to this kind of storage is not left to work it out alone.
Three campuses hold the distributed storage. The Great Plains Network connects them to the wider region.
Supported by National Science Foundation award OAC-2502799.
Workshops, trainings, and community events across the region.
Virtual
Join us for an interactive workshop to learn about GP-STOR and get started as a beta user
Iowa State University
Learn how to migrate AI/ML workflows to the Nautilus platform, part of the National Research Platform
Kansas State University
Learn how to migrate AI/ML workflows to the Nautilus platform, part of the National Research Platform
South Dakota State University
Learn how to migrate AI/ML workflows to the Nautilus platform, part of the National Research Platform
University of Arkansas
Learn how to migrate AI/ML workflows to the Nautilus platform, part of the National Research Platform
Virtual
This webinar will give instructors an introduction to leveraging the large distributed computing resources available through the National Research Platform (NRP)
No upcoming events at this time.
Four ways onto the same storage, each matching how research data already moves
Mount GP-STOR directly in high-throughput computing jobs on the Open Science Grid and the National Research Platform.
Publish datasets to the Open Science Data Federation and have them served out to jobs wherever those jobs land.
Managed, high-performance transfers for moving large collections between GP-STOR, campus storage, and collaborators elsewhere.
Browse, upload, and share through a web interface, for the work that does not belong on a command line.
The workloads the tiered design was built around
The solid-state tier is built for streaming data straight into AI/ML algorithms, rather than staging it somewhere else first.
Land simulation output on the object tier as it is produced, then distribute the curated results with Globus.
Stream instrument data to the high-speed tier for preprocessing and analysis, then keep it alongside everything else.
Give students hands-on time with the same cyberinfrastructure their field runs on, in coursework and in research projects.
Cyberinfrastructure for a region where it has been hard to build
Deploying advanced infrastructure in rural regions, where awareness and literacy of high-throughput computing are still emerging.
Building an engineering and facilitation workforce able to design and run an interstate research platform.
Focused on the campuses that have had the least access to infrastructure like this, including PUIs and tribal colleges.
Supporting the industrial sectors the region depends on, including agriculture and advanced materials.
Where the project stands today, and what comes between here and open access.
Q3 2026: Infrastructure acquisition
Finalize specifications and procure infrastructure for GP‑STOR.
Q4 2026: Receive hardware
Delivery and rack/cabinet intake at sites; begin inventory and staging.
Q4 2026-Q1 2027: Deploy and configure
Install CEPH clusters across sites, configure replication, pools, and monitoring.
Q1 2027: Deploy storage interfaces
Enable access methods such as a web interface and mounting on National Research Platform.
Q2 2027: Beta users
Onboard early adopters for real-world testing and performance tuning.
Q3 2027: Open access & trainings
Public access opens, training sessions held, and operational support transitions to steady‑state.
Q4 2027: Convene user group
Bring together early stakeholders and beta participants to solicit feedback on service design and policies.
GP-STOR is in the acquisition and deployment phase, with open access scheduled for 2027. Talk to your campus CI lead now so your storage needs are known before beta onboarding begins.