Ready to Scale

UC Riverside's Surging Demand for High-Performance Computing

A Clear & Present Need

A comprehensive review has identified a significant and growing number of UCR research groups whose work is primed for acceleration. These researchers require immediate access to scalable GPU and TPU resources to push the boundaries of science and innovation.

16

Research Groups

9

High-Demand Projects

Demand Level Breakdown

Pioneering Research Across Diverse Fields

The need for advanced computation spans the entire campus, driving innovation in fields from artificial intelligence and robotics to bioinformatics and systems design.

Spotlight on High-Impact Research

Multi-Discipline Acceleration

Rajiv Gupta

Requires GPU acceleration for three distinct, complex projects: training ML models for multi-robot path planning, analyzing large-scale genomic sequences in bioinformatics, and using LLMs with reinforcement learning to optimize code layouts.

Accelerating Drug Discovery

Mingxun Wang

Needs interactive, multi-GPU (4+ A100s) and surge capacity (16+ A100s) to increase experiment iterations from once per day to dozens, dramatically speeding up the development of diffusion models for drug discovery.

✍️

Next-Generation AI Models

Greg Ver Steeg

Research into novel "discrete diffusion models" for parallel text generation is currently blocked by a lack of compute. A single model requires an estimated 1,000 GPU hours to train and validate at a competitive scale.

Campus-Wide Strategic Opportunities

GCP Renewal

Unlocks Campus Potential

Hybrid Cloud Bursting

Offload peak demand from on-premise HPCC and BCOE clusters.

Secure Computing

Provide compliant enclaves for sensitive data (PII, medical).

Hosted Research Tools

Enable public-facing websites and tools with server-side compute.

Democratized GPU Access

Offer paid Colab access for courses and smaller projects.

LLM & GenAI APIs

Streamline access to Gemini and other foundation models.