UC San Diego Datahub & Research Platform

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DataHub Downtime 1:00-2:30 P.M. Nov. 17th

On November 17th, we detected mass networking errors to DataHub. We have since reset the Hub's database which has appeared to fix the issue. Users who were running pods during the outage will have to wait for their pods to self-terminate (~1 hour after 2:30) before they can launch another one. We apologize for any inconvenience the outage may have caused. -DSMLP Staff

Student Resources

Instructor Resources

Request Datahub/DSMLP - Instructional Technology Request (CINFO)
Scope of Support & Guidelines for Usage
Instructor Guidance for Datahub/DSMLP
Educational Technology Services Instructional Github
Blink Documentation
Datahub Grading Tools

nbgrader
Sync assignments and grades with your Canvas course: nb2canvas

Overview

UC San Diego's Datahub & Research Cluster provide access to research-class CPU/GPU resources for coursework, formal independent study, and student projects.

Instructors may request Datahub/Research Cluster for their courses via an Instructional Technology Request (CINFO), with students automatically receiving access 1-2 days prior to start of each term. Access to Datahub is described in the ITS Instructional Technology Guides.

Jupyter Notebooks

Web-based Jupyter notebooks allow users to combine live code, equations, visualizations and narrative text for data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and more. DSMLP's Jupyter notebooks offer straightforward interactive access to popular languages and GPU-enabled frameworks such as Python, R, Pandas, PyTorch, TensorFlow, Keras, NLTK, and AllenNLP.

Machine Learning

Complex ML workflows are supported through terminal/SSH logins, background batch jobs, and a full Linux/Ubuntu CUDA development suite. Users may install additional library packages (e.g. conda/pip, CRAN) as needed, or can opt to replace the default environment entirely by launching their own custom Docker containers.

High-speed cluster-local storage houses student workspaces, course files, and common training corpora (e.g. CIFAR, ImageNet).

If you would like to acknowledge this service in any publications, please use the text below.

The Data Science and Machine Learning Platform is operated by IT Services (ITS), with additional financial contributions from Cognitive Science and Jacobs School of Engineering