An integrated multi-hazard risk framework applied to the US high-voltage grid finds tropical cyclone wind causes the highest expected daily damage ($137M) while tornadoes drive the largest downstream economic losses ($4.93B/day), with a compound freezing rain/wind scenario producing the most severe
DOPD: A Dynamic PD-Disaggregation Architecture for Maximizing Goodput in LLM Inference Serving.IEEE Transactions on Services Computing.2026;19(2):1134-1147
2 Pith papers cite this work. Polarity classification is still indexing.
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This research agenda argues that cloud-native architectures, microservices, autoscaling, and emerging trends like serverless inference and federated learning are required to make large language models efficient and scalable.
citing papers explorer
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A Comparative Multi-Hazard Risk Assessment of the US High-Voltage Transmission Network
An integrated multi-hazard risk framework applied to the US high-voltage grid finds tropical cyclone wind causes the highest expected daily damage ($137M) while tornadoes drive the largest downstream economic losses ($4.93B/day), with a compound freezing rain/wind scenario producing the most severe
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Cloud-native and Distributed Systems for Efficient and Scalable Large Language Models -- A Research Agenda
This research agenda argues that cloud-native architectures, microservices, autoscaling, and emerging trends like serverless inference and federated learning are required to make large language models efficient and scalable.