High-Performance Computing (HPC) refers to the practice of aggregating computing power in a way that delivers much higher horsepower than traditional computers and servers. HPC, or supercomputing, is like standard workstation computing, only more powerful. It is a way of processing huge volumes of data at very high speeds using multiple computers and storage devices as a cohesive fabric. HPC makes it possible to explore and find answers to some of the world’s biggest problems in science, engineering, and research.
Today, HPC is used to solve complex, performance-intensive problems—and organizations are increasingly moving HPC workloads to the cloud. Ursa Major
is UCR’s HPC in the cloud is and it lowers the economics of product development and research because it requires fewer prototypes, accelerates testing, and decreases time to discovery.
UCR’s Research Computing can facilitate our researchers and their lab’s access to the following HPC resources:
UCR's Ursa Major Research Computing Service.
Ursa Major is ITS Campus subsidized and is no cost to UCR Researcherse. Ursa Major is powered by Google Cloud and is a game-changing development for UCR’s Researcher and their Research. This service is designed to drive research at an increased pace and bring more grants and funding to the University. This service is a massively scalable and innovative approach to providing Research Computing resources, tools, and support as summarized below: Reach out and get started today!
Each Ursa Major Cluster is connected to an Ursa Major’s virtually unlimited-sized parallel high-speed storage as well as the Ursa Major’s General Research Storage.
Reach out to the Research Computing team to help you get your lab up and running todayresearch-computing@ucr.edu
Nautilus is a heterogeneous, distributed cluster, with computational resources of various shapes and sizes made available by research institutions spanning multiple continents! Check out the Cluster Map to see where the nodes are located.
This is a no-cost resource at the moment and can be used to run many types of machine learning and research workloads.
National and Academic Supercomputing Centers via the ACCESS program formally known as XSEDE. This provides no-cost access to supercomputer resources through a proposal process.