Information Commons Computational Environments

The Research Analysis Environment (RAE) provides research teams with a professionally managed, secure, collaborative environment in which to manage files containing sensitive data. RAE also provides remote desktop capability with applications (e.g., Azure Data Studio, SSMS, Jupyter Notebook, RStudio, Stata, SAS) that allow investigators to view, manipulate, and save their data entirely in a protected environment without requiring files to be stored locally.

Choose if:

• You require specific licensed software on RAE for your analysis.
• You intend to extract the data you need and download it onto your computer.
• You would like a managed environment pre-configured for working with IC data with minimal setup.

Access: 

For detailed information on how to access and work with IC on RAE, see the Information Commons on RAE Wiki.

Wynton HPC is a large, shared high-performance compute cluster (SGE) at UCSF, available to all researchers and tailored to diverse biomedical and health science computing needs.

Choose If:

• Your computer's memory, storage, and CPU/GPU are not sufficient for your analysis.
• You conduct most of your analysis using Python.

Wynton Transition:

IC Wynton is currently being migrated to the new IC FAC environment. For detailed information, see the Wynton Transition Instructions and the IC-specific guidance on the IC FAC Wiki.

Information Commons on FAC (IC FAC) is a new on-premises computational environment that extends the UCSF Information Commons onto the Facility for Advanced Computing (FAC) and Core HPC infrastructure. IC FAC is designed to support secure, high-performance data science and AI workflows, from exploratory analysis to model development and deployment.

IC FAC provides interactive CPU and GPU resources, scalable storage, and direct, fast access to Information Commons data assets within a PHI-compliant environment. It is well-suited for researchers developing and testing computational pipelines, working with large structured and unstructured datasets, and training or running AI and machine learning models.

IC FAC is currently launching in alpha and beta testing, with broader availability planned following the testing period.

Choose If:

• You need on-premises, high-performance computing with interactive CPU and GPU access
• You work with large-scale clinical, imaging, or text data and want data-local compute
• You are developing, testing, or fine-tuning AI/ML or LLM workflows
• You want a flexible environment where you can install your own Python/R packages or web-based tools
• You plan to transition workloads from IC on Wynton to a modern FAC-based environment

Access:

IC FAC is currently available by request during the beta testing period.
For access details, documentation, and tutorials, see the Information Commons on FAC Wiki.

IC AWS Secure is an AWS Secure Enterprise Cloud-based computational environment featuring PHI-compliance, accelerated computing with CPU nodes and GPUs, and flexible configuration options for research. Includes various data storage solutions and the ability to launch AWS EMR clusters (Apache Spark with Yarn) for distributed computing.

Choose If:

• Your project is funded, and you have budgeted for computation (IC AWS Secure is recharge-based).
• Your project has uniquely heavy computation requirements that can't be fulfilled by other environments.
• You do not have long-term plans to purchase and maintain your own hardware for research.

Access:

For detailed information on how to access and work with IC on AWS SEC, see the Information Commons on AWS Secure Wiki.