3 papers
cs.DC2026
From Barrier to Bridge: The Case for AI Data Center/Power Grid Co-Design
Noman Bashir, Rob Sherwood, Le Xie +1
For over a century, the electric grid has relied on a single statistical assumption: \emph{load diversity}, the principle that the uncorrelated demands of millions of small consume…
eess.SY2026
Workload composition smooths aggregate power demand while sustaining short-horizon ramps in AI data centers
Subir Majumder, Minlan Yu, Le Xie
Artificial intelligence (AI) is driving rapid growth in electricity demand, yet the grid-facing power dynamics of AI data centers remain poorly understood. Here we show that, in sh…
eess.SY2025
EdgeSight: Enabling Modeless and Cost-Efficient Inference at the Edge
ChonLam Lao, Jiaqi Gao, Ganesh Ananthanarayanan +2
Traditional ML inference is evolving toward modeless inference, which abstracts the complexity of model selection from users, allowing the system to automatically choose the most a…