HPC Research Showcase
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.
Tamar Schlick (FAS/CIMS) and her research team (Qiyao Zhu, Swati Jain, and Shuting Yan) have been using the Greene HPC cluster to address our global health crisis by advancing practical approaches to COVID-19 treatment. The team 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 Tamar’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 with larger RNA systems and also drug/RNA interactions to further investigate the drug binding potential of the covid-19 RNA gene.
Researchers (Edwin Gerber, Olivier Pauluis, Shafer Smith, Laure Zanna) in the Courant's Center for Atmosphere Ocean Science (CAOS) are undertaking challenging research projects that rely heavily on HPC to perform computationally demanding simulations of various parts of the climate system. They 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.
These include, to name just a few projects, 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 the how hurricane size and intensity are changing with global warming.
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.
The Green HPC cluster enables researchers (Joshua Tucker, Richard Bonneau, Jonathan Nagler) at the Center for Social Media and Politics (CSMaP)
to analyze Terabytes of social interactions, such as “likes” and retweeted from the Twitter Decahose. These analysis allow them to answer a multitude of long-standing social science questions.
The CPU and GPU resources of the Greene cluster enable CSMaP researchers to ask both applied and theorietical questions, examining, for example, 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.