Research Infrastructure: MRI: Acquisition of a Big Data HPC Cluster for Interdisciplinary Research and Training

An award is made to the University of California, Riverside (UCR) to acquire a Big Data High-Performance Computing (BD-HPC) cluster designed to enable novel and transformative research, outreach and training activities that are highly relevant to the environment and society. The system will be managed by UCR's HPC Center (HPCC) that serves a broad and diverse user population distributed across colleges and departments.

As a highly shared resource, the instrument will enable a large number of NSF-funded programs, including those aiming to improve practices in agriculture, environmental protection, technology development and industry. Extensive educational and training activities are integrated to disseminate multidisciplinary concepts of Big Data Science. These outreach components will educate the public about the impact of Big Data Science on the environment, economy and society.

The HPCC supports many undergraduate and graduate classes in a wide range of disciplines. Its resources are also instrumental for the development of new courses and programs in various data science areas. A high percentage of students in these classes and programs are from populations that are traditionally underrepresented in STEM disciplines.

The availability of adequate computing and its beneficial impact on educational programs will attract outstanding students to computational and quantitative undergraduate and graduate programs. Combined with UCR’s diverse ethnicity and research mission, this investment will benefit a wide array of translational research directions and technology-based economic development initiatives.

The new BD-HPC cluster will enable novel research that cannot be performed on UCR’s current research computing infrastructure or community cyberinfrastructure (CI), while also offering sufficient capacity to ensure support of ongoing research with greatly improved performance. Both current and new research addresses fundamental problems in a highly interdisciplinary environment bridging a broad array of science and engineering disciplines in basic and translational research.

Grand challenge questions asked include: How do genetic and population dynamics determine phenotypic and evolutionary diversity? How can large-scale precision data be translated into improved stress and pathogen tolerance to feed a growing world population, and to develop interventions for reducing the rate and impact of environmental changes, natural disasters and climate change?

How can quantitative modeling lead to high-performance molecules, materials, and help prevent wildfires and predict earthquakes? UCR researchers working on these problems are from a wide range of research specializations, including environmental science, agriculture, biology, chemistry, physics, engineering, computer science, statistics and applied mathematics.

Since their research relies heavily on high-throughput and computational modeling approaches, the BD-HPC cluster will permit new computational approaches for solving these research problems.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.