Ursa Major Guidelines

Overview

Ursa Major is the University of California, Riverside’s (UCR) cloud computing resource for research, providing scalable access to Google Cloud Platform (GCP). These guidelines are designed to ensure the equitable, responsible, and efficient use of Ursa Major resources while supporting high-impact research at UCR.

This document outlines the following:

  • Eligibility and Access
  • Resource Allocation Policies (Explore & Advanced Tiers)
  • Application Processes and Review Cycles
  • Usage Guidelines and Compliance
  • Support, Privacy, and Security Measures
  • Future Planning for Ursa Major Resources

1. Eligibility & Access

Who Can Use Ursa Major?

Ursa Major is available to all UCR-affiliated researchers, including:

  • Faculty members
  • Postdoctoral researchers
  • Graduate students (if affiliated with a research project)
  • Staff members conducting research-related activities

How to Get Started

To use Ursa Major, researchers must:

  1. Have an active UCR NetID.
  2. Complete the required Ursa Major training and acknowledgment process.
  3. Submit an allocation request according to their research needs (details below).

Researchers will be assigned either an Explore Tier or Advanced Tier allocation based on their proposal and needs.


2. Resource Allocation Model

Ursa Major operates on a tiered resource allocation system to balance equitable access while supporting diverse research requirements.

2.1 Allocation Tiers

Explore Tier (Default Allocation)

The Explore Tier is designed for introductory research, small-scale projects, and early experimentation with cloud resources.

Key Details:

  • $1,500 credit allocation (~3 months of usage at ~$15/day)
  • Covers Compute Engine, Cloud Storage, Cloud Functions, AI/ML tools (Vertex AI), and other core GCP services
  • No application review required (automatic approval)
  • Usage alerts at 50%, 75%, 95%, and 100% of the budget

Researchers can monitor their usage through the Ursa Major dashboard.


Advanced Tier (For Larger Projects)

The Advanced Tier is intended for researchers with high-performance computing (HPC), GPU-intensive workloads, and large-scale cloud research projects.

Key Details:

  • Requires application & Research Advisory Board (RAB) subgroup review
  • Allocations are granted on a quarterly cycle with defined application deadlines
  • Advanced allocations are not processed immediately but reviewed as a group to ensure fair distribution
  • Applicants must submit a proposal detailing their resource needs, research impact, and estimated costs

2.2 Advanced Tier Application Process & Review Structure

🔹 How & When to Apply for an Advanced Allocation

Advanced allocations follow a structured quarterly application and review process, ensuring fairness and predictability.

Initial Allocation Period (March – June 2025)

  • The first Advanced Tier application window opens March 1, 2025.
  • Applications must be submitted by March 14, 2025 for consideration.
  • Reviews will take place between March 15 – March 25, 2025.
  • Allocations will be approved and available starting April 1, 2025.

Quarterly Allocation Cycles

After the initial allocation period, Advanced Tier applications will follow a standard quarterly review:

Application Deadline Review Period Allocations Start
March 14 March 15 – March 25 April 1 – June 30
June 14 June 15 – June 25 July 1 – September 30
September 14 September 15 – September 25 October 1 – December 31

Applicants will receive notification of acceptance or denial within 5 business days after the review period ends.


🔹 Research Advisory Board Subgroup Review & Allocation Limits

All Advanced allocation applications will be reviewed by a subgroup of the Research Advisory Board (RAB) that evaluates requests based on research merit, impact, feasibility, and available resources.

Review Criteria:

  • Scientific and academic merit of the research project
  • Impact and feasibility of the proposed resource use
  • Remaining GCP resource availability for that allocation cycle

The total available budget per quarter is a key factor in approval decisions. If resource demands exceed the available funding, projects may receive partial allocations or be deferred to the next cycle. The RAB review panel will ensure that allocations are distributed equitably while maximizing research impact.


3. What Happens if You Run Out of Resources?

If a research project reaches the limit of its allocation, the following applies:

  1. Explore Tier Users:
    • Receive a 7-14 day grace period for data retrieval.
    • Can apply for an Advanced allocation before reaching 95% usage.
  2. Advanced Tier Users:
    • Must submit a renewal request before the next review cycle if continued access is required.
    • If budget is depleted before the next allocation cycle, researchers can request temporary reduced-access extensions (reviewed case-by-case).

4. Support & Assistance

Who to Contact for Help

For technical or allocation issues, contact Ursa Major Research Support: 📩 Email: research-computing@ucr.edu

Response Time Expectations

Issue Type Expected Response Time
Routine Questions 1-2 business days
Technical Troubleshooting 2-4 business days
Advanced Allocation Review Quarterly review cycle
Urgent Issues (e.g., shutdown prevention) Same-day escalation

5. Security, Data Privacy, & Future Planning

Data Ownership & Privacy

  • All research data remains the property of the researcher/UCR.
  • No unauthorized access or monitoring—Google & UCR do not claim ownership or review your data.
  • Government/legal requests for data require researcher notification unless legally restricted.

Planning Beyond the Current Contract

The current Ursa Major contract expires in 11 months. The university is actively planning for the next phase of cloud resource availability. Updates will be provided as decisions are made regarding renewals, funding, and resource expansions.


6. Next Steps: How to Proceed

New User? Start with an Explore Tier Request
Need More Resources? Apply for an Advanced Tier Allocation
Questions? Contact research-computing@ucr.edu

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