Scientific Computing and Data
Partnering with researchers to advance scientific discovery
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Led by Dean for Scientific Computing Patricia Kovatch, the Scientific Computing team partners with researchers to advance science by providing tools, resources, and assistance to researchers across institutions around the globe.
Advance your Science
Utilize our services to facilitate your research, data, or compute power.
High Performance Computing
The primary asset for Scientific Computing is the supercomputer, Minerva. The HPC resource, upgraded in 2021, utilizes
- 24,912 Intel Platinum in different generations including
- 8568Y+ 2.3GHz, 8358 2.6 GHz, and 8268 2.9 GHz compute cores with 1.5TB of memory per node
- 96 cores or 64 cores or 48 cores per node with two sockets in each node
- 196 H100 GPUs, 32 L40S, 40 A100 GPUs, 48 V100 GPUs, 440 terabytes of total memory
- 32 petabytes of spinning storage accessed via IBM’s Spectrum Scale/General Parallel File System (GPFS)
- > 2 petaflops of CPU compute power and ~ 8 petaflops for GPU compute power
Minerva has contributed to over 1,700 peer-reviewed publications since 2012.
Research Data Services
We partner with scientists to conduct their research via independent data collection, capture, and analysis.
- eRAP is a web-based interactive tool for data entry and reporting. Custom databases are rapidly developed for longitudinal single and multi-site studies.
- REDCap* is a secure web application for building and managing online surveys and databases. Track data manipulation, user activity, export procedures, scheduling, calendaring, and branching logic.
- Data Ark utilizes FAIR principles to provide regularly updated high-quality data sets for reusability in research.
All applications are HIPAA compliant.
*Please note that our current build of REDCap is not 21 CFR 11 compliant.
Mount Sinai Data Warehouse
The Mount Sinai Data Warehouse provides researchers access to data on over 11 million patient records in the Mount Sinai Health System Epic Electronic Health Record (EHR).
- In total there are over 87 million patient encounters recorded in Epic
- The MSDW ecosystem is Epic and OMOP-centric
- Clinical data is extracted from the Epic Caboodle and Clarity databases, transformed to the OMOP Common Data Model (CDM)
- Data is located on the Minerva High Performance Computing cluster
Request your own custom data set or utilize self-service query tools to search the data.
Supported by grant UL1TR004419 from the National Center for Advancing Translational Sciences, National Institutes of Health.