UC San Diego: From Coffee Cart to Educational Computing Platform

In classic UC San Diego fashion, an overheard conversation at a campus coffee cart has turned into an interdisciplinary project that’s making computing-intensive coursework more exciting while saving well over $1 million dollars so far. The effort gives UC San Diego graduate and undergraduate students—and their professors—better hardware and software ecosystems for exploring real-world, data-intensive and computing-intensive projects and problems in their courses.

Larry Smarr.
Larry Smarr, Distinguished Professor Emeritus, Department of Computer Science and Engineering at the UC San Diego Jacobs School of Engineering.

It all started while UC San Diego computer science and engineering professor Larry Smarr was waiting for coffee in the “Bear” courtyard at the Jacobs School of Engineering a little more than three years ago. While standing in line, Smarr overheard a student say, “I can’t get a job interview if I haven’t run TensorFlow on a GPU on a real problem.”

While this one student’s conundrum may sound extremely technical and highly specific, Smarr heard a general need; and he saw an opportunity. In particular, Smarr realized that innovations coming out of a U.S. National Science Foundation (NSF) funded research project he leads—the Pacific Research Platform (PRP)—could be leveraged to create better computing infrastructure for university courses that rely heavily on machine learning, data visualizations, and other topics that require significant computer resources. This infrastructure would make it easier for professors to offer courses that challenge students to solve real-world data- and computation-intensive problems, including things like what he heard at the coffee cart: running TensorFlow on a GPU on a real problem.

Fast forward to 2022, and Smarr’s spark of an idea has grown into a cross-campus collaboration called the UC San Diego Data Science/Machine Learning Platform or the UC San Diego JupyterHub. Through this platform, the inexpensive, high-performance computational building blocks combining hardware and software that Smarr and his PRP collaborators designed for use in computation-intensive research across the country are now also the backbone of dynamic computing ecosystems for UC San Diego students and professors who use machine learning, data visualization, and other computing- and data-intensive tools in their courses. The platform has been widely used in every division on campus, including with courses taught in biological sciences, cognitive science, computer science, data science, engineering, health sciences, marine sciences, medicine, music, physical sciences, public health and more.

It’s a unique, collaborative project that leverages federally funded computing research innovations for classroom use. To make the jump from research to classroom applications, a creative and hardworking interdisciplinary team at UC San Diego came together. UC San Diego’s IT Services / Academic Technology Services stepped up in a big way. Senior architect Adam Tilghman and chief programmer David Andersen led the implementation effort, with leadership and funding support from UC San Diego CIO Vince Kellen and Academic Technology Senior Director Valerie Polichar. The project has already helped the campus avoid well over $1 million dollars in cloud-computing spend, according to Kellen.

At the same time, the project gives the UC San Diego community tools to encourage the back-and-forth flow of students and ideas between classroom projects and follow-on research projects.

“Our students are getting access to the same level of computing capacity that normally only a researcher using an advanced system like a supercomputer would get. The students are exploring much more complex data problems because they can,” said Smarr, who was also the founding director of the California Institute for Telecommunications and Information Technology (Calit2), a UC San Diego / UC Irvine partnership. Calit2 is now expanding to also include UC Riverside.

Comments are closed.