HewlettPackard/dc-rl
SustainDC is a set of Python environments for Data Center simulation and control using Heterogeneous Multi Agent Reinforcement Learning. Includes customizable environments for workload scheduling, cooling optimization, and battery management, with integration into Gymnasium.
This project helps data center operators and sustainability managers simulate and optimize data center operations for energy efficiency and reduced carbon footprint. You provide details about your servers, cooling systems, and workload demands. The system then outputs optimal strategies for scheduling workloads, managing cooling, and utilizing auxiliary batteries, helping you make decisions that lower energy consumption and carbon emissions.
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Use this if you are a data center operations manager, sustainability engineer, or energy efficiency specialist looking to test and implement strategies for more sustainable data center management.
Not ideal if you need a plug-and-play solution for immediate control of an existing data center without simulation or if you are not interested in exploring reinforcement learning-based optimization.
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Aug 25, 2025
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