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Tactic: Use Energy-Aware Scheduling
Tactic sort:
Awesome Tactic
Type: Architectural Tactic
Category: green-ml-enabled-systems
Title
Use Energy-Aware Scheduling
Description
Energy-aware scheduling refers to a strategy that optimizes the scheduling of machine learning tasks. It dynamically schedules tasks or processes based on the current energy requirements and system conditions. The objective of an energy-aware dynamic scheduling policy is to make efficient use of available computational resources.
Participant
Software Designer
Related software artifact
< unknown >
Context
Machine Learning
Software feature
< unknown >
Tactic intent
Improve energy efficiency by dynamically managing workers to maximize the overall utilization in distributed systems
Target quality attribute
Resource Utilization
Other related quality attributes
Performance, Energy Efficiency
Measured impact
Sun et al show that energy-aware scheduling schedules 6 % more workers compared to other methods.
Source
Yuxuan Sun, Sheng Zhou, and Deniz Gündüz. 2020. Energy-Aware Analog Aggregation for Federated Learning with Redundant Data. In ICC 2020-2020 IEEE International Conference on Communications (ICC). IEEE, 1–7. (DOI: https://doi.org/10.1109/ICC40277.2020.9148853)Graphical representation
