A diffusion model is used to augment rewards in deep reinforcement learning for coordinated AIGC workload scheduling and energy management across distributed data centers.
Game-theoretic deep reinforcement learn- ing to minimize carbon emissions and energy costs for AI inference workloads in geo-distributed data centers,
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Joint Energy Management and Coordinated AIGC Workload Scheduling for Distributed Data Centers: A Diffusion-Aided Reward Shaping Approach
A diffusion model is used to augment rewards in deep reinforcement learning for coordinated AIGC workload scheduling and energy management across distributed data centers.