UC Riverside's Surging Demand for High-Performance Computing
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
The need for advanced computation spans the entire campus, driving innovation in fields from artificial intelligence and robotics to bioinformatics and systems design.
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.
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.
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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.
Unlocks Campus Potential
Offload peak demand from on-premise HPCC and BCOE clusters.
Provide compliant enclaves for sensitive data (PII, medical).
Enable public-facing websites and tools with server-side compute.
Offer paid Colab access for courses and smaller projects.
Streamline access to Gemini and other foundation models.