Gaurav Shah, Director of Academic Technologies for Bentley University, and Clifton Chow, Senior Research Technology Consultant, present at the 2023 EDUCAUSE conference.

Oct 11 2023

EDUCAUSE 2023: How One University Moved Research Computing to the Cloud

Bentley University research technologists share their cloud migration journey.

As higher education institutions increasingly embark on data-intensive research projects, high-performance computing is a necessity. In some cases, universities are replacing traditional computing environments with scalable cloud infrastructure.

At EDUCAUSE 2023 in Chicago, Clifton Chow, senior research technology consultant for Bentley University, and Gaurav Shah, director of academic technologies, spoke about their university’s journey migrating research computing to the cloud.

What Is Research Computing?

First, Shah outlined why there’s such a demand for research computing in higher education.

“Research computing is any service that provides infrastructure and resources for helping faculty doing computational analysis, especially in the field of Big Data,” he said. In higher education, he said, research computing allows faculty to analyze multiple data sources simultaneously as well as large-scale data sets.

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Research computing programs also benefit the institutions themselves. They can be selling points for those interviewing for faculty jobs, as many expect these resources to be available, particularly at larger institutions. Robust research computing programs also can help institutions win external grants and funding for research projects.

Research computing’s infrastructure must balance intensity, characterized by complex algorithms and millions of rows of data, with frequency, or long and short bursts of demand, Shah said. At a baseline level, security, scalability, size, flexibility and cost are all key components of research computing.

Why Bentley University Moved Research Computing to the Cloud

According to Chow, at the outset of this project, Bentley University’s research computing department was operating its data center out of one room with multiple cores and GPU nodes to handle high speed and high performance with multiple servers.

This infrastructure posed some challenges, Chow said, which prompted the move to the cloud.

“It was costly,” he said. “Our administration had made a decision to end this on-campus infrastructure and they asked us to come up with a plan.”

The increasing size of the data sets also prompted the move to the cloud.

DISCOVER: Find out how to optimize your university’s connection to the cloud.

“Now, we’re putting in healthcare data, and healthcare data comes in all shapes and sizes,” Chow said. “There are electronic health records, and there are administrative records. Databases are very expensive, and they cover anywhere from 10 to 100 million lives. Being able to store that is also a major challenge.”

Additionally, most faculty members preferred using a Windows environment, and the on-campus research computing operated on Linux, which required extra training. Maintenance was time-consuming, as IT staffers would have to walk to a separate building on campus to troubleshoot, change hardware and manage upgrades. The on-premises infrastructure also lacked customization options, meaning faculty requiring more advanced resources sometimes had to use other organizations’ resources.

Faculty Personas Helped Determine the Cost of Cloud Migration

In planning the cloud migration, the team first sought input from other similarly sized institutions to determine how they were approaching things like research computing environment management, cloud versus physical storage, security, storage and backups, and training and support. They also considered financial models as they related to cloud offerings from different vendors. Costs seemed high, and the team had to justify the price tag to stakeholders.

The team then developed faculty personas with qualities of those who would end up using the research computing resources.

“We took a step back to understand our faculty use cases, and only then we would have more clarity on where we want to go next,” Shah said. “What we ended up with was the crucial point in our journey. We said, ‘Let’s look at all the projects we’ve done so far. What are the goals? What are the needs? What operating system they want? Do they need machine learning, parallel processing and so on?’”

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The team developed four personas: Jimmy, a user running advanced machine learning and using multiple CPUs or GPUs and high-speed storage for large data sets; Xiu, who runs some machine learning projects but not at an advanced level; Bob, who just wants a fast machine to run advanced statistical analyses with more memory and storage for data processing; and Marcia, a user who has done all the research and wants to share it through public dashboards.

“This was very crucial for us, and when we went through this exercise, most of the faculty are Bob,” Shah said. “They just wanted a fast machine. We were trying to build a machine for Jimmy, and that’s where the cost implications were coming from.”

Ultimately, the Bentley University team opted for a Microsoft Azure environment, which includes the Azure Virtual Desktop, Azure HPC Pack and Azure Machine Learning.

Best Practices for Managing Research Computing Cloud Environments

Shah and Chow monitor faculty usage of the system and determine how to manage costs accordingly. Quarterly faculty check-ins help them determine who is using the resources and whether they can be recycled for another use.

They’ve also established a formal intake process in which faculty members fill out a form to identify their research needs so that the research computing team can identify the best environment for their projects. This has helped manage costs, Shah said.

WATCH: See how the University of Florida supports research computing with a robust network.

Conversations with academic leadership around governance, equity and funding help ensure that the resources are being used responsibly and equitably across campus and across faculty members.

Finally, Shah said, the university tries to stay open to alternatives. Sometimes, a faculty member might just need a faster desktop computer. In other cases, an on-premises rack might be the more appropriate option.

“Be open,” he said. “This is not one shot and then you’re all in the cloud, and that’s the beauty of cloud: You can scale up and you can scale down. That’s why it’s definitely worth going into the cloud.”

Keep up with EdTech: Focus on Higher Education’s coverage on our EDUCAUSE event page and via X (formerly Twitter).

Photography by Amy McIntosh

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