most citedGame-Theoretic Deep Reinforcement Learning to Minimize Carbon Emissions and Energy Costs for AI Inference Workloads in Geo-Distributed Data Centers

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cs.DC2025

Sustainable Carbon-Aware and Water-Efficient LLM Scheduling in Geo-Distributed Cloud Datacenters

Hayden Moore, Sirui Qi, Ninad Hogade +3

In recent years, Large Language Models (LLM) such as ChatGPT, CoPilot, and Gemini have been widely adopted in different areas. As the use of LLMs continues to grow, many efforts ha…

cs.DC2024★ 1 cited

GreenFaaS: Maximizing Energy Efficiency of HPC Workloads with FaaS

Alok Kamatar, Valerie Hayot-Sasson, Yadu Babuji +6

Application energy efficiency can be improved by executing each application component on the compute element that consumes the least energy while also satisfying time constraints.…

cs.DC2024★ 1 cited

Game-Theoretic Deep Reinforcement Learning to Minimize Carbon Emissions and Energy Costs for AI Inference Workloads in Geo-Distributed Data Centers

Ninad Hogade, Sudeep Pasricha

Data centers are increasingly using more energy due to the rise in Artificial Intelligence (AI) workloads, which negatively impacts the environment and raises operational costs. Re…