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Tactic: Implement Energy-Aware Optimization Framework
Tactic sort:
Awesome Tactic
Type: Architectural Tactic
Category: green-ml-enabled-systems
Title
Implement Energy-Aware Optimization Framework
Description
Integrate an energy-aware optimization framework into enterprise AI workflows. The framework dynamically balances performance and energy use by adjusting optimization parameters and trade-off weights in real time. It ensures accuracy targets are met while lowering energy consumption, making it suitable for large-scale and continuous AI workloads.
Participant
AI engineers, enterprise system architects
Related software artifact
AI models in enterprise systems
Context
Large-scale enterprise environments with continuous AI workloads
Software feature
Training and inference processes of AI models
Tactic intent
Reduce energy consumption while maintaining acceptable model accuracy
Target quality attribute
Energy efficiency
Other related quality attributes
Accuracy, scalability, performance
Measured impact
Validated in enterprise settings: 30.6% reduction in energy consumption with only 0.7% accuracy loss
Source
Saumya Dash (2025). Green AI: Enhancing Sustainability and Energy Efficiency in AI-Integrated Enterprise Systems (DOI: https://doi.org/10.1109/ACCESS.2025.3532838)Graphical representation
