Queen’s and Simon Fraser University (SFU) have partnered to pursue federal funding for a supercomputing initiative that could position Canada among global leaders in artificial intelligence (AI) infrastructure.
The partnership is part of the federal governments Sovereign Compute Infrastructure Program (SCIP), which is expected to allocate up to $926 million toward building advanced computing systems across the country. If successful, Queen’s would host a top 10 leadership class supercomputer, while SFU would operate a complementary, top-25 system designed to work alongside it, allowing users to scale projects from smaller workloads at SFU to large-scale processing at Queen’s.
The partnership also builds on broader efforts by Queen’s to expand its role in AI, including recent investments in talent, such as the hiring of former NVIDIA engineer Ian Karlin, and infrastructure to support large-scale research.
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In an interview with The Journal, Vice-Principal (Research) Nancy Ross said she’s “been working together with the institutional folks over the last couple of years positioning the University to be able to take this project on.”
Ross said the initiative is intended to address a gap between Canada’s AI expertise and its computing capacity, noting many researchers rely on systems outside the country to run large-scale projects.
“What folks have been able to do to make sure they can run AI is buying time on clouds [remote computing servers run by companies like Amazon or Google] outside of Canada, which is very expensive,” Ross said. “And then it’s not secure.”
According to Ross, this reliance raises concerns around both cost and data sovereignty, particularly in sectors such as energy, healthcare, and national security.
The proposed system would be accessible to researchers, government, and private-sector companies, supporting large-scale projects ranging from drug discovery to climate modelling.
While Queen’s brings experience designing advanced computing systems, SFU contributes operational expertise from running large-scale infrastructure, including Canada’s largest public system serving thousands of researchers and industry partners.
The Journal also spoke with Ryan Grant, an associate professor in electrical and computer engineering and technical lead on the project. He reiterated that the partnership reflects a strategic alignment between the two institutions, describing the collaboration as a “natural alliance.”
“We’re creating a nice pipeline for academic users and industrial R&D [research and development] to be able to use one system at a smaller scale, then we come up and go larger and larger scale,” Grant said.
The initiative is additionally tied to broader economic and geopolitical considerations. Both Ross and Grant pointed to the need for Canada to develop domestic AI infrastructure rather than relying on foreign providers.
“We want to make sure that we are AI producers of the future, not AI consumers of the world economy,” Grant said.
He added that relying on external systems could pose risks if access to AI technologies becomes restricted. Beyond research and industry, the project is expected to create opportunities for students, particularly in engineering and computing fields.
Grant also highlighted opportunities for training and collaboration between students, researchers, and industry partners.
If successful, Ross said the project could significantly shape the future of research and innovation at Queen’s and across Canada. “I think it’s really going to be an exciting time for this University,” Ross said.
Grant said the proposal is currently in a competitive funding stage, following an earlier statement of interest submitted by Queen’s in 2025. A full federal call for proposals is expected in April, and institutions across Canada are anticipated to submit competing bids.
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AI, Queen's supercomputing, Simon Fraser University, Supercomputing
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