HPC research is expanding our knowledge in all academic areas

Below is a snapshot of just a few of the groundbreaking research projects currently taking advantage of Greene and NYU's other high performance computing resources.

Understanding the Structural Biophysics of the SARS-CoV-2 Virus

Using the Greene HPC cluster, Tamar Schlick (FAS/CIMS) and her research team—Qiyao Zhu, Swati Jain, and Shuting Yan—made groundbreaking advances in understanding the structural biophysics of the SARS-CoV-2 virus and the molecular mechanisms by which the virus infects humans.

The team focuses on understanding the structure and mechanisms of the RNA frameshifting element (FSE). The FSE is one of the highly conserved regions of coronaviruses, which critically affects viral replication and viral protein production, making it a major drug target.

The computational power of Greene made it possible for Schlick’s team to run microsecond long, state-of-the-art Molecular Dynamics (MD) simulations of RNA systems at atomic resolution, explore different lengths and compositions of RNA (including mutant systems), and obtain meaningful statistics on the dynamics of various structural elements.

The team is continuing to study larger RNA systems as well as drug/RNA interactions to further investigate the drug-binding potential of the COVID-19 RNA gene.

Climate Modeling

Researchers Edwin Gerber, Olivier Pauluis, Shafer Smith, and Laure Zanna are able to use hundreds of CPUs and the fast interconnect on the Greene HPC cluster to run complex atmosphere and ocean models that will enable our researchers to improve our understanding of key processes in the climate system.

A few projects include understanding global changes in precipitation patterns, data-driven approaches to representing unresolved (sub-grid scale) momentum transport in the atmosphere and ocean, predicting coastal sea level changes (including storm surges) along the US East Coast, and improving our understanding of how hurricane size and intensity are changing with global warming.

Holodeck Multi-Modality

NYU's Holodeck team uses high performance computing to create a new multi-modality experiential supercomputer. The Holodeck is making it possible to witness the performances of musicians and dancers across several continents in one cohesive experience.

These new simulated artistic realities created by the Holodeck use VR, motion capture suits, and digital metronomes to sync the timing of performances around the world.

The Holodeck team is also creating new educational technologies by engineering fast-paced games to better understand brain function and reaction time.

Studying the Sounds of the City

Juan Pablo Bello and his research team of Anish Arora, R. Luke DuBois, Oded Nov, and Claudio Silva use the expanded HPC resources to advance their studies of sound and noise pollution in NYC.

From jackhammers and sirens to the honking horns of busses, the study's 56 sensors gathered decades-worth of audio data and sound-pressure levels in the form of 10-second clips.

Processing and storing this data on HPC storage enables the team to work through their data at a much faster pace and advance their study of New York's noisy soundtrack.

Additional Information

Sounds of New York City (SONYC)

Mapping the Genome of Rice

Researchers at the NYU Center for Genomics and Systems Biology (CGSB) will be able to use the Greene cluster state-of-the art software analysis tools and seamlessly integrate their workflows with large genomic data sets.

This integration will enable Michael Purugganan and his team to investigate genetic variation in rice, which could lead to accelerated genetic improvement in this important world crop.

Advancing rice genomics and producing improved rice varieties offer the promise of helping address global food security, especially in the face of worldwide climate change.

Twitter Decahose

The Green HPC cluster enables Center for Social Media and Politics (CSMaP) researchers Joshua Tucker, Richard Bonneau, Jonathan Nagler to analyze Terabytes of social interactions, such as “likes” and retweets from the Twitter Decahose. These analyses allow them to answer a multitude of long-standing social science questions.

Twitter logo

The CPU and GPU resources of the Greene cluster enable CSMaP researchers to ask both applied and theoretical questions, from how voters develop opinions in a democracy to measuring attitudinal and behavioral outcomes in relation to COVID-19 political pronouncements and COVID-induced economic hardships.

Large numbers of GPU provided by Greene are used to analyze the network information (URL-sharing, retweeting, and following behavior) of politically-interested Twitter users to look at how ideology affects information exchange and relations to elites on Twitter, requiring significant computation on the adjacency matrix generated from the network.