Ursa Major

Modern Research requires advanced computing and data management resources

The University of California, Riverside is proud to announce its latest partnership with Google Cloud Platform (GCP), code-named Ursa Major, designed to provide the research computing support and resources necessary for our researchers to advance their work and unlock new opportunities for innovation and growth.

Ursa Major Resources

Through Ursa Major, UCR’s researchers will have access to the following new and exciting resources:

  • Research Workstations: Researchers can access high-performance workstations with ample memory and CPU or storage capabilities.
  • Auto-scaling HPC Clusters: Researchers can access cutting-edge high-performance computing clusters, equipped with the latest CPUs, GPUs, and large memory configurations.
  • Research AI and Machine Learning Services: Researchers can leverage Vertex.ai, Google’s AI and Machine Learning platform, as well as other services, to support their research endeavors.
  • Secure Research Storage: Researchers will have access to secure and optimized storage solutions, ensuring the safekeeping of their valuable research data.

This partnership with Google Cloud Platform is a major milestone for UCR, representing a significant investment in the future of research at our university. Our Research Computing Team is committed to providing a secure research computing infrastructure and research support services that will drive increased research output, grant funding, campus income, and prestige. This, in turn, will lead to the hiring of new faculty, positioning UCR as a leading R1 research university.

Ursa Major Resource Allocation Framework

UCR’s strategic approach to Ursa Major resource allocation ensures equitable access for researchers, prioritizing projects with significant potential for impact. The framework supports both high-value and exploratory projects through a tiered system, optimizing cloud resource distribution and enhancing research capabilities.

  • Explore Tier: Allocated 20% of our total allocation pool. Designed for novel, long-term uses without a time-bound element, encouraging exploratory and innovative research.
  • Project Tier: Receives 40% to 60% of our allocation pool. This tier is both value and time-bound, intended for substantial research projects that demonstrate potential value through grants, papers, or publications. Allocation scheduling is strategic to accommodate and optimize large project resources.
  • Campus Tier: Initially allocated 20% of the pool, with potential to expand to 40%. Reserved for the Campus ITS Infrastucture, this tier allows flexible usage within its limit, supporting internal technological advancements and infrastructure needs.

Requesting a URS Major Resource Allocation:

Submit your Ursa Major resource allocation request through our:

The Research Computing Team will review your project’s allocation requet and available resources to approve your allocation. Once approved, you will receive an email with your allocation details and you can begin using your resources.

Monitoring Allocations:

To ensure the efficient use of resources and to support our researchers in the best possible manner, UCR’s Research Computing team has implemented a comprehensive monitoring and optimization strategy for Ursa Major resource allocations. This approach enables us to track resource usage in real-time, identify bottlenecks, and optimize allocations to support a wide range of research activities effectively.

Researchers and the ITS team can access detailed analytics and insights into their resource usage through the following Ursa Major Dashboards:

Dashboard Description
Cloud Storage Dashboard Provides insights into the storage utilization across all projects, including data ingress and egress, helping to optimize storage strategies.
Disks Dashboard Offers a detailed view of disk usage and performance metrics, enabling teams to manage and scale disk resources efficiently.
Infrastructure Summary Dashboard A comprehensive overview of the entire GCP infrastructure, highlighting usage patterns, available resources, and potential optimization opportunities.
VM Instances Dashboard Tracks the performance and usage of virtual machine instances, facilitating the effective management of compute resources.
Logs Dashboard Enables tracking of application and system logs, crucial for debugging and understanding system behaviors.
Allocation Spend Dashboard Coming Soon: A future dashboard that will provide detailed insights into the allocation spend, helping to track and manage budgetary aspects of projects.

Contact us for help or to learn more! research-computing@ucr.edu - UCR Research Computing Slack