Low-cost and high-performance execution of nowadays computing-intensive applications will not be possible without large-scale heterogeneous computing platforms. The huge computing power of such platforms raises the problem of the electrical energy consumed by such platforms. One of the key issues to achieve high-performance in such platforms is task-scheduling. Among the heuristics-based compile-time dependent-task scheduling heuristics, duplication-based list scheduling heuristics give the earliest finish time of the application tasks. Unfortunately, due to the additional computing cost required by duplication, these heuristics consume more computing power that leads to more electrical energy consumption. Energy-efficiency and green-computing turn the attention to the need for new generations of energy-aware task-scheduling algorithms. This paper presents a duplication reduction mechanism that can be applied to any schedule produced by a duplication-based scheduling algorithm. The aims of the proposed mechanism are to keep the same finish time of the scheduled application tasks, to keep the lower-bound time-complexity of the heuristics-based dependent task scheduling algorithms, and to significantly reduce the energy consumed by task-duplication. The mechanism is called Green. Green was applied to four of the most-recent and well-known duplication-based list-scheduling algorithms. The experimental results based on computer simulation utilizing C# language for large sets of both randomly generated and three real-world applications graphs show that Green can significantly reduce the energy consumed by each algorithm.

如果没有大规模的异构计算平台，就不可能以低成本，高性能的方式执行当今计算密集型应用程序。这样的平台的巨大计算能力提出了这样的平台消耗的电能的问题。在此类平台上实现高性能的关键问题之一是任务计划。在基于启发式的编译时相关任务调度启发式方法中，基于重复的列表调度启发式方法提供了应用程序任务的最早完成时间。不幸的是，由于重复需要额外的计算成本，这些启发式方法消耗了更多的计算能力，从而导致了更多的电能消耗。能源效率和绿色计算将注意力转移到对新一代的能源感知任务调度算法的需求上。本文提出了一种复制减少机制，该机制可应用于基于复制的调度算法产生的任何调度。所提出的机制的目的是保持与计划的应用程序任务相同的完成时间，保持基于启发式的依赖任务计划算法的下限时间复杂性，并显着减少任务复制所消耗的能量。该机制称为绿色的。Green被应用到四个最新的，最著名的基于重复的列表调度算法中。基于使用C＃语言进行的计算机模拟的实验结果，对大量随机生成的图形和三个实际应用图形均进行了实验，结果表明Green可以显着降低每种算法所消耗的能量。