Overview
Technology Infrastructure for Data Exploration (TIDE) provides CSU researchers with access to research-class CPU & GPU resources and was built with a focus on AI and machine learning. While AI and machine learning workflows are the focus of TIDE, they are not a requirement, meaning that other workloads amenable to containerization are welcome.
TIDE will initially be available for testing and feedback from the science drivers before becoming generally availble to all researchers in the CSU.
For the latest updates, check out the TIDE timeline.
Getting Access
Learn more about getting access at Using TIDE.
JupyterHub
TIDE offers a dedicated JupyterHub instance that offers simplifies access to TIDE resources in a browser-based development environment. JupyterHub is the latest web-based interactive development environment for notebooks, code, and data. Its flexible interface allows users to configure and arrange workflows in data science, scientific computing, computational journalism, and machine learning. Languages such as Python, R, and Julia are available along with Pandas, PyTorch, and TensorFlow libraries.
Containerization
In addition to the JupyterHub, more complex jobs can be created and run as software containers directly on the TIDE cluster. Navigate to the containerization Quickstart to learn how to run containerized software on TIDE. Requests for batch access to TIDE can be made by submitting a TIDE Support Request.
TIDE is supported by the Research & Cyberinfrastructure group within the IT Division. TIDE is funded by NSF Award #2346701