About High Performance Computing

Scientific Computing and Data partners with scientists to accelerate scientific discovery. Led by Dean for Scientific Computing and Data Patricia Kovatch, the Scientific Computing team provides tools, resources, and assistance to researchers across institutions around the globe.


Minerva High Performance Computing Platform

The primary asset for Scientific Computing is the supercomputer Minerva. The HPC resource, upgraded in 2020, utilizes 14,304 Intel Gold 8168 24C, 2.7 GHz compute cores (48 cores per node with two sockets in each node), 286 nodes with 192 GB of memory per node, 65.7 terabytes of total memory, 350 terabytes of solid-state storage and nearly 30 petabytes of spinning storage accessed via IBM’s Spectrum Scale/General Parallel File System (GPFS) for a total of 1.2 petaflops of compute power. Minerva has contributed to over 1,200 peer-reviewed publications in seven years. Click here for a quickstart guide to access Minerva directly. See also:

For Minerva User Training Classes and Archives, click here.


Data Resources

Through Minerva, researchers may access volumes of data:

Data Ark (Data Commons)

The Data Ark team downloads, organizes and performs quality assurance and quality control on research data used by Mount Sinai data scientists. The team also manages the data access process, answers questions on the data, and updates to the latest versions of the data sets. Click here to learn more about the Data Ark and how to access it.

Mount Sinai Data Warehouse (MSDW)

The Mount Sinai Data Warehouse (MSDW) collects clinical, operational, and financial data for use in clinical and translational research, as well as quality and improvement initiatives. Click here to learn more about MSDW and how to use it.


Research Services

Scientific Computing and Data Science supports many avenues for conducting research:

  • REDCap is a secure web application for building and managing online surveys and databases
  • eRAP is a highly customizable web-based interactive tool for data entry and reporting
  • HHEAR and HADatAc are public data collections of longitudinal health data

Learn more about additional research services or about current research.



Still have questions about High Performance Computing? Contact us at hpchelp@hpc.mssm.edu