Power analysis of embedded software: a first step towards software power minimization
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special issue on low-power design
An Optimal Scheduling Algorithm Based on Task Duplication
IEEE Transactions on Computers
A Genetic Algorithm for Multiprocessor Scheduling
IEEE Transactions on Parallel and Distributed Systems
Practical Multiprocessor Scheduling Algorithms for Efficient Parallel Processing
IEEE Transactions on Computers
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Both the heterogeneity of the computing environment and the complexity of various application tasks lead to heterogeneous computing. The purpose of heterogeneous computing is to obtain the best executing effect for a parallel task running on the parallel processing system by putting emphasis on the difference between the parallel task and system, and exploring the optimal matching between the task and system. Currently, in heterogeneous computing, the scheduling method only for time optimization is quite mature, but the research on the executing method both for time and energy optimization is very few. This paper aims at the high performance computing and green computing, and pays more attention to the scheduling problem for a parallel task in heterogeneous computing environment. We present the heterogeneous task model, the heterogeneous computing speed matrix and the heterogeneous computing power matrix. Based on the idea that energy can be unified to time, this paper proposes some heuristic executing algorithms to achieve both time and energy optimization for a parallel task on heterogeneous system. Finally, a case study shows the feasibility and efficiency of proposed algorithms.