Energy-Aware Task Scheduling for NoC-based Dynamic Voltage Scalable System
Date Issued
2009
Date
2009
Author(s)
Hung, Ssu-Wen
Abstract
Energy-aware task assignment and scheduling over a many-core network-on-chip (MC-NoC) platform is investigated. For real time applications, time slacks of a preliminary task schedule may be exploited to conserve energy. This can be accomplished by leveraging the dynamic voltage scaling (DVS) technique to slow down clock frequency of certain cores so long as the deadline is met. In this Thesis, the task of fine-tuning an existing task assignment and schedule and using DVS to lower overall energy consumption is formulated as a graph-theoretic maximum weight clique (MWC) problem. An efficient heuristic algorithm is proposed to systematically solve this problem. A unique feature of our approach is concurrently applying DVS to slow down execution of multiple tasks to achieve better energy saving. Extensive simulations are performed to compare this proposed algorithm against leading energy-aware task scheduling algorithm and DVS algorithm. Our algorithm exhibits a 22% more energy saving than the EAS algorithm. As for energy saving in DVS process, our MWC-based method provides a 97% saving improvement over the PV-DVS algorithm.
Subjects
low power
task scheduling
multi-core
DVS
NoC
SDGs
Type
thesis
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