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Journal Articles International Journal of Parallel Programming Year : 2022

Energy-Efficient Partial-Duplication Task Mapping under multiple DVFS schemes


On multicore platforms, reliable task execution, as well as low energy consumption, are essential. Dynamic Voltage/Frequency Scaling (DVFS) is typically used for energy savings, but with a negative impact on reliability, especially when the applied frequency is low. Using high frequencies, required to meet reliability constraints, or replicating tasks increases energy consumption. To reduce energy consumption, while enhancing reliability and satisfying real-time constraints, we propose a hybrid approach that combines distinct reliability enhancement techniques, under task-level, processor-level and systemlevel DVFS. Our task mapping problem jointly decides task allocation, task frequency assignment, and task duplication, under real-time and reliability constraints. This is achieved by formulating the task mapping problem as a Mixed Integer Non-Linear Programming (MINLP) problem, and equivalently transforming it into a Mixed Integer Linear Programming (MILP), that can be optimally solved. From the obtained results, the proposed approach achieves better energy consumption, finding solutions, when replication approaches fail.
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Dates and versions

hal-03907885 , version 1 (06-01-2023)



Minyu Cui, Angeliki Kritikakou, Lei Mo, Emmanuel Casseau. Energy-Efficient Partial-Duplication Task Mapping under multiple DVFS schemes. International Journal of Parallel Programming, 2022, 50 (2), pp.267-294. ⟨10.1007/s10766-022-00724-7⟩. ⟨hal-03907885⟩
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