基于多核处理器的K线程低能耗的任务调度优化算法

K-threaded Low Energy-consuming Task Scheduling Optimization Algorithm Based on Multi-core Processors

针对具有独立DVFS的多核处理器系统,提出了一种K线程低能耗模型的并行任务调度优化算法(Tasks Optimization based on Energy-Effectiveness Model,TO-EEM)。与传统的并行任务节能调度相比,该算法的主要目标是不仅通过降低处理器频率来减少处理器瞬时功耗,而且结合并行任务间的同步互斥所造成的线程阻塞情况,合理分配线程资源来减少线程同步时间,优化并行性能;保证任务在一定的并行加速比性能前提下,提高资源利用率,减少能耗,达到程序能耗和性能之间的折衷。文中进行了大量模拟实验,结果证明提出的任务优化模型算法节能效果明显,能有效降低处理器的功耗,并始终保持线性加速比。

Based on multi-core processor system with independent DVFS module,this paper proposed a K-threaded lowpower optimal algorithm for parallel task modeling which is tasks optimization based on Energy-Effectiveness Model（TO-EEM）.Compared with the traditional energy-efficient scheduling of parallel tasks,the main solution for reducing processor power consumption reduces synchronization duration between threads and optimizes parallelism performance not only by decreasing the instantaneous frequency of processors,but also rationally allocating thread resources.Regarding tasks with a certain acceptable speedup performance,we improved resource utilization and reduced energy consumption to reach a compromise between power consumption and program performance.The paper carried a lot of simulation experiments,and the result presents that the proposed task optimization scheduling model has a effective impact on reducing processor power consumption,and still maintains a linear speedup.