“This is the microscope and the telescope and the linear accelerator of the 21st century all in one,” said Emmanuel Candès, faculty director of Stanford Data Science and courtesy EE professor, describing his team’s latest installation. Marlowe, a state-of-the-art GPU-based computational instrument, will begin accepting applications from the entire Stanford research community on its website on Jan. 15, 2025. 

 

Candès can barely contain his excitement. In its ability to churn through computations as never before, Marlowe will put Stanford at the forefront of data science. This “superpod” comprises 248 Nvidia H100 graphical processing units (GPUs), the chips fueling the research and development of AI innovators like OpenAI. 

 

Under the stewardship of the Office of the Vice Provost and Dean of Research, the university will invest $30 million to purchase hardware, recruit a team of research data scientists, support Marlowe’s operational needs, and facilitate collaboration opportunities – all important to get the most out of Marlowe in a rapidly evolving field. Marlowe is now being tested at Stanford Research Computing data center, where it will be housed for the foreseeable future. 

 

Since Marlowe’s installation this summer, a technical team has partnered with beta testers to refine the system's performance. Even in the early days, one of those beta testers, Professor Gordon Wetzstein said, “Marlowe has already turbocharged my research and made possible something that wasn't just three months ago.” 

 

“I fully expect Marlowe will be oversubscribed on day one,” Candès added.

 

Excerpted from 'Stanford welcomes first GPU-based supercomputer.'