Virtual Machines for Clinical Research

Virtual Machines for Clinical Research offer a dedicated environment for researchers to prototype code and applications that cannot run on the HPC. These VMs provide the flexibility to scale according to your needs and are backed by a specialized team within the Research Computing Systems Engineering group, ensuring comprehensive support. For cost efficiency, the hosted Research virtual machines are run on-premises, with both Linux and Windows servers available.

Benefits:

  • Highly available
  • Scalable
  • Backup options available upon request
  • Managed and supported by systems administrators
  • Customizable

The VMs are hosted on a dedicated, highly available cluster utilizing VMware technologies. They are backed up and can be configured with various levels of reporting and monitoring to ensure uptime and reliability. The Research Computing Systems Engineering group handles core operating system maintenance, including critical security updates, allowing researchers to focus solely on their research rather than system administration.

These VMs can be customized to meet specific research needs with a wide range of applications and tools. They offer a practical alternative to physical research workstations, which can occupy space and become outdated quickly. VMs also provide more flexibility; for instance, increasing memory or CPU can be done without rebooting, and storage upgrades are seamless, saving valuable research time with minimal risk of data loss.

Service Area
Research Systems Engineering
Available to
Medicine Campus
Service Steps

Faculty members can request a VM for personal or research group use. Graduate students and postdoctoral candidates must request machines through their advisor or PI to streamline management. To utilize the service, request through TeamDynamix under the categories: Red Hat Enterprise Linux or Windows Server.

Example Use Case
  • A researcher requires compute resources to run MATLAB for processing experimental results.
  • A researcher needs compute resources to process and analyze studies with DICOM images.