collaborators

5 papers

cs.DC2026

Power-Flexible AI Data Centers: A New Paradigm for Grid-Responsive Compute

Chris Williams, Philip Colangelo, Ayse Coskun +15

The rapid expansion of artificial intelligence (AI) infrastructure is driving unprecedented growth in electricity demand from data centers. Traditional power-system planning treats…

cs.AI2026

PALS: Power-Aware LLM Serving for Mixture-of-Experts Models

Can Hankendi, Rana Shahout, Minlan Yu +1

Large language model (LLM) inference has become a dominant workload in modern data centers, driving significant GPU utilization and energy consumption. While prior systems optimize…

cs.DC2026

A Practical Two-Stage Framework for GPU Resource and Power Prediction in Heterogeneous HPC Systems

Beste Oztop, Dhruva Kulkarni, Zhengji Zhao +2

Efficient utilization of GPU resources and power has become critical with the growing demand for GPUs in high-performance computing (HPC). In this paper, we analyze GPU utilization…

cs.LG2025

UniCoMTE: A Universal Counterfactual Framework for Explaining Time-Series Classifiers on ECG Data

Justin Li, Efe Sencan, Jasper Zheng Duan +3

Machine learning models, particularly deep neural networks, have demonstrated strong performance in classifying complex time series data. However, their black-box nature limits tru…

cs.DC2025

Turning AI Data Centers into Grid-Interactive Assets: Results from a Field Demonstration in Phoenix, Arizona

Philip Colangelo, Ayse K. Coskun, Jack Megrue +12

Artificial intelligence (AI) is fueling exponential electricity demand growth, threatening grid reliability, raising prices for communities paying for new energy infrastructure, an…