Grid Impacts of Datacenters

Students: Grant Wilkins, Obi Nnorom, Jr.

PIs: Philip Levis, Computer Science and Electrical Engineering; Juan Rivas-Davila, Electrical Engineering; and Ram Rajagopal, Civil & Environmental Engineering and Electrical Engineering

Electricity used for today’s machine learning training workloads can peak at 10 megawatts or even multiples of that. Then, when the computers stop processing to communicate their results, their power demand drops to about a fifth of their peak load in microseconds. These huge, synchronized load swings introduce enormous problems to the electric grid. This project seeks to research and build a power supply mechanism that ensures a computing rack’s load does not change quickly due to its energy storage. Data center operators have told the researchers that such a power supply would be much better than their current strategies to deal with the problem.