MRI: Acquisition of a high-performance computing resource to enhance research and undergraduate education at the College of Staten Island

Cuny College Of Staten Island, Staten Island NY

Investigators

Abstract

This award supports the acquisition of a high-performance computing (HPC) cluster to enhance research and undergraduate education at the College of Staten Island (City University of New York). The HPC cluster will serve a diverse pool of faculty to boost computational research in areas ranging from biology and biomedicine to computer science, engineering, and materials science. By aiding studies characterizing large biomolecules, this resource will help garner an understanding of basic life processes relevant to human health and the environment. Likewise, researchers working in computer science, engineering, and materials science will benefit in their development of new algorithms for the analysis and extraction of information from complex and large digital datasets. Coupled with the application of modern simulation techniques to investigate minerals of geophysical relevance, such endeavors will lead to a deeper insight into the composition of the Earth's mantle. The acquisition will also support and expand the educational activities leveraging high-performance computers as tools for learning and training, including coursework in computational and STEM disciplines by offering hands-on computing activities to high school students and teachers. The computational instrument will consist of two computing ‘super’ nodes with a hybrid architecture comprising of both central and graphics processing units (CPUs and GPUs), integrated with a large-capacity intelligent storage system. This HPC resource is tailored to support a range of data-heavy parallel workflows, which will enable investigators to augment scientific knowledge in areas where experimental science is reaching its limits, and where progress is intrinsically driven by computational studies. This cluster will enable: (i) novel computationally-enhanced cryo-electron microscopy techniques to unravel the structure and dynamics of biomolecules; (ii) modern atomistic simulations to compute binding affinities of chemical compounds to protein receptors and hence discover new drug therapies; (iii) development of new data mining and artificial intelligence (AI) algorithms for the analysis and predictive modeling of complex networks, high-dimensional data and 3D objects; and (iv) exploit quantum mechanical calculations to predict the properties of rock-forming minerals of geophysical relevance. The HPC cluster will also enable educators to augment formal classroom education in computational disciplines, stimulate undergraduate curriculum development, and support graduate and undergraduate research projects. Access to this resource will prepare students and future generation of scientists for diverse careers in research and industry that are increasingly relying on the use of computers, cloud technologies, and parallel computing. 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.