The Scientific Computing group partners with scientists to accelerate scientific discovery.

With our highly tuned high performance computing and data ecosystem, we enable researchers to ask and answer new scientific questions.

The HPC resource, upgraded in 2020 with a total of 1.5 petaflops of computational power, consists of >20,000 compute cores, 350 terabytes of flash and 21 petabytes of parallel file system storage, and has been cited in over 1,170 papers in seven years.

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Minerva Quick Start

Minerva uses the Secure Shell (ssh) protocol and Two Factor authentication. For more about connecting, click here.

Request Access

All Minerva users must submit a request for access. Requests for external collaborators can be submitted here.


Training Archive

Minerva Training Group offers training and town hall meetings. For recent trainings, click here. For archives, click here.



Haven’t found what you are looking for? Visit our Frequently Asked Questions. To read more, click here.

Data Ark (Data Commons)

Data Ark includes both public and Sinai-generated data sets. This initiative is led by Associate Professor Paul O’Reilly and Dean for Computing Patricia Kovatch, and supported by the Department of Genetics and Genomic Sciences and Scientific Computing. Access any of the seven data sets for research.

Mount Sinai Data Warehouse

The MSDW collects clinical, operational, and financial data for use in clinical and translational research, as well as quality and improvement initiatives. See options to work with MSDW analysts to compose custom SQL queries for research, so you can conduct more research with better data.

Minerva is HIPAA Compliant

All users are required to read the HIPAA policy and complete the Minerva HIPAA Agreement Form on an annual basis or risk account deactivation. Click here to read more about HIPAA Compliance.

Complete HIPAA Form

Remember to acknowledge Mount Sinai in your work. 

An acknowledgement of support from the Icahn School of Medicine at Mount Sinai should appear in a publication of any material, whether copyrighted or not, based on or developed with Mount Sinai-supported computing resource.

Click here for suitable acknowledgements to add to your work.