Journal ArticleDOI
Scheduling Precedence Constrained Tasks with Reduced Processor Energy on Multiprocessor Computers
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TLDR
Investigation of energy-efficient scheduling of sequential tasks with precedence constraints on multiprocessor computers with dynamically variable voltage and speed makes initial contribution to analytical performance study of heuristic power allocation and scheduling algorithms for precedence constrained sequential tasks.Abstract:
Energy-efficient scheduling of sequential tasks with precedence constraints on multiprocessor computers with dynamically variable voltage and speed is investigated as combinatorial optimization problems. In particular, the problem of minimizing schedule length with energy consumption constraint and the problem of minimizing energy consumption with schedule length constraint are considered. Our scheduling problems contain three nontrivial subproblems, namely, precedence constraining, task scheduling, and power supplying. Each subproblem should be solved efficiently so that heuristic algorithms with overall good performance can be developed. Such decomposition of our optimization problems into three subproblems makes design and analysis of heuristic algorithms tractable. Three types of heuristic power allocation and scheduling algorithms are proposed for precedence constrained sequential tasks with energy and time constraints, namely, prepower-determination algorithms, postpower-determination algorithms, and hybrid algorithms. The performance of our algorithms are analyzed and compared with optimal schedules analytically. Such analysis has not been conducted in the literature for any algorithm. Therefore, our investigation in this paper makes initial contribution to analytical performance study of heuristic power allocation and scheduling algorithms for precedence constrained sequential tasks. Our extensive simulation data demonstrate that for wide task graphs, the performance ratios of all our heuristic algorithms approach one as the number of tasks increases.read more
Citations
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A genetic algorithm for task scheduling on heterogeneous computing systems using multiple priority queues
TL;DR: The experimental results for large-sized problems from a large set of randomly generated graphs as well as graphs of real-world problems with various characteristics show that the proposed MPQGA algorithm outperforms two non-evolutionary heuristics and a random search method in terms of schedule quality.
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Bi-objective workflow scheduling of the energy consumption and reliability in heterogeneous computing systems
TL;DR: A novel bi-objective genetic algorithm (BOGA) to pursue low energy consumption and high system reliability for workflow scheduling and performs significantly better in terms of finding the spread of compromise solutions.
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Maximizing reliability with energy conservation for parallel task scheduling in a heterogeneous cluster
TL;DR: A novel Reliability Maximization with Energy Constraint (RMEC) algorithm, which incorporates three important phases, including task priority establishment, frequency selection, and processor assignment, which can effectively balance the tradeoff between high reliability and energy consumption.
Journal ArticleDOI
Thermal-Aware Task Scheduling for Energy Minimization in Heterogeneous Real-Time MPSoC Systems
TL;DR: A two-stage energy-efficient temperature-aware task scheduling scheme for heterogeneous real-time multiprocessor system-on-chip (MPSoC) systems that minimizes the system dynamic energy consumption under the constraint of task deadlines and reduces the temperature-dependent system leakage energy consumption.
Journal ArticleDOI
Thermal-aware correlated two-level scheduling of real-time tasks with reduced processor energy on heterogeneous MPSoCs
Junlong Zhou,Junlong Zhou,Jianming Yan,Kun Cao,Yanchao Tan,Tongquan Wei,Mingsong Chen,Gongxuan Zhang,Xiaodao Chen,Shiyan Hu +9 more
TL;DR: A two-level thermal-aware energy-efficient scheduling algorithm for real-time tasks on DVFS-enabled heterogeneous MPSoC systems is developed considering the constraints of task deadlines, task precedences, and chip peak temperature limit.
References
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Proceedings ArticleDOI
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