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Author

Chaojie Zhang

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Review Aug 2026

Slasher: Power Flexibility for Cloud Datacenters

Datacenters consume many megawatts of power, and regularly encounter scenarios that require modulating their power draw. These scenarios include datacenter infrastructure failures, power grid failures, grid services, and more, spanning a diverse range of requirements in terms of the power magnitude, the scope of the reduction, the notice time, and other dimensions. To address these scenarios, we have built Slasher, a general system for modulating the power of \azure datacenters to handle scenarios ranging from individual racks to regional multi-datacenter grid events. Slasher coordinates datacenter resources with the goal of meeting power targets while minimizing negative impact on hosted workloads. In this paper, we review the main power modulation scenarios, characterize the power reduction levers using data from production cloud datacenters, describe Slasher's system architecture, and formulate the cloud datacenter power modulation control problem. We also develop a high-fidelity datacenter simulator and propose a workload impact model, using them to design and evaluate power control algorithms.

Liuzixuan Lin, Fiodar Kazhamiaka, A. Kumbhare et al. · 0 citations
Preprint Aug 2026

Architectural Implications of Agentic AI Workflows

This work organizes agentic workflows in a taxonomy and presents its first architectural characterization with a production study at Microsoft Azure and a controlled study of open-source frameworks, showing that agentic execution is fragmented and heterogeneous.

Jirong Yang, Peizhe Liu, Chaojie Zhang et al. · 2 citations