【摘要】：異構(gòu)并行系統(tǒng)是高性能低功耗計算機(jī)系統(tǒng)的主要發(fā)展趨勢之一,異構(gòu)并行系統(tǒng)下的低功耗研究是近年來學(xué)者研究的熱點問題。由于動態(tài)電壓頻率調(diào)整(DVFS,Dynamic Voltage and Frequency Scaling)技術(shù)以及任務(wù)調(diào)度在能耗優(yōu)化方面的潛能,近年來不少基于DVFS技術(shù)的任務(wù)調(diào)度算法被提出并取得了不錯的效果。然而,這些算法沒有綜合考慮任務(wù)的執(zhí)行時間和能耗,無法做到時間和能耗的權(quán)衡優(yōu)化,且這些算法在其任務(wù)模型中使用平均值表示任務(wù)的執(zhí)行時間和通信時間,這種表示方法不夠精確,會對任務(wù)調(diào)度的性能產(chǎn)生影響。異構(gòu)并行系統(tǒng)下基于時間-能耗權(quán)重比的任務(wù)調(diào)度算法(Weight-ratio-based Task Scheduling,WTS)與DVFS技術(shù)相結(jié)合,它同時考慮時間和能耗這兩個性能指標(biāo),能夠根據(jù)時間-能耗的權(quán)重比為每個任務(wù)選擇合適的處理器及電壓級別,做到時間和能耗的權(quán)衡優(yōu)化,獲取相較于現(xiàn)有算法更優(yōu)的系統(tǒng)加權(quán)性能。在任務(wù)初次分配階段,WTS算法為每個任務(wù)選擇使其加權(quán)性能提升值最大的處理器及電壓級別;在任務(wù)再次優(yōu)化分配階段,該算法隨機(jī)選擇一個任務(wù),并將該任務(wù)重新分配給相對于原有分配有系統(tǒng)加權(quán)性能提升的處理器及電壓級別,使系統(tǒng)的加權(quán)性能進(jìn)一步提升。同時,WTS算法考慮到任務(wù)執(zhí)行時間以及任務(wù)間通信時間的不確定性,在任務(wù)模型中使用近似權(quán)重代替平均值,以獲取更優(yōu)的調(diào)度性能。為證明WTS算法的有效性,仿真實驗將其與兩個現(xiàn)有算法在時間、能耗、系統(tǒng)加權(quán)性能以及相對性能提升等方面進(jìn)行了對比,實驗結(jié)果顯示,WTS算法能做到時間和能耗的權(quán)衡優(yōu)化,使系統(tǒng)的加權(quán)性能更優(yōu),同時在時間和能耗單個性能指標(biāo)方面也具有優(yōu)勢。
[Abstract]:Heterogeneous parallel systems are one of the main trends in the development of high performance and low power computer systems. The research on low power consumption in heterogeneous parallel systems is a hot issue in recent years. Due to the potential of dynamic voltage-frequency adjustment (DVFS,Dynamic Voltage and Frequency Scaling) and task scheduling in energy optimization, many DVFS-based task scheduling algorithms have been proposed and achieved good results in recent years. However, these algorithms do not consider the task execution time and energy consumption, and can not achieve the balance of time and energy consumption optimization, and these algorithms use the average in their task model to represent the execution time and communication time of the task. This representation is not accurate enough to affect the performance of task scheduling. In heterogeneous parallel systems, the task scheduling algorithm (Weight-ratio-based Task Scheduling,WTS) based on time-to-energy weight ratio is combined with DVFS technology, which takes into account both time and energy consumption. It can select the appropriate processor and voltage level for each task according to the weight ratio of time-to-energy consumption, and optimize the trade-off of time and energy consumption, and obtain the better system weight performance than the existing algorithms. In the initial assignment phase, the WTS algorithm selects the processor and voltage level whose weighted performance increases the maximum for each task. In the task reoptimization phase, the algorithm randomly selects a task, and reassigns the task to the processor and voltage level, which improves the weighted performance of the system compared with the original assignment, which further improves the weighted performance of the system. At the same time, considering the uncertainty of task execution time and inter-task communication time, WTS algorithm uses approximate weight instead of average value in task model to obtain better scheduling performance. In order to prove the effectiveness of the WTS algorithm, the simulation experiment compares it with the two existing algorithms in terms of time, energy consumption, system weighting performance and relative performance improvement. The experimental results show that: The WTS algorithm can optimize the balance of time and energy consumption, and make the weighted performance of the system better. At the same time, it also has advantages in the single performance index of time and energy consumption.
【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TP301.6

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本文編號：2436992