摘要
在移动设备和嵌入式设备中,能量的供给是十分有限的,它受限于能量供给设备的容量和节电能力的大小.在能量受限的环境下,电池所提供的能量不足以使系统达到最优的性能目标.因此,提出了一种能量受限环境下最优化预取性能的方法.该方法通过软件控制的手段,能在有限的能量供给条件下达到最优的性能.该方法是基于动态频率可调的CPU和存储器的.根据CPU和存储器的忙闲情况,通过插入频率调节指令,指导调节CPU和存储器的频率,使得预取优化的两个性能指标(一是时间,二是处理器收益)在一定的能量约束条件下达到最优.对该问题建立了详细的模型及模拟环境,并通过一组以数组访问为主的测试程序验证了该方法的有效性.模拟结果表明,该方法对能量受限预取优化问题是有效的.
In mobile and embedded devices, the energy supply is strictly constrained with the battery capacity and energy saving ability. In these energy-constrained settings, the available energy budget is not sufficient to meet the optimal performance objective. This paper presents an energy-constrained software prefetching optimization approach, which can obtain the optimal performance under the limited energy resource. The approach is based on DVS-enabled CPU and memory. Through inserting frequency-scaling instructions, CPU and memory frequencies are simultaneously adjusted to meet two performance objectives （one is the time; the other is the processor gain） under a given energy constraint. A detailed analytical model is built and then the effectiveness of the approach is validated by a set of array-intensive applications. Experimental results show that the approach is effective for energy-constrained prefetching optimization problem.
出处
《软件学报》
EI
CSCD
北大核心
2006年第7期1650-1660,共11页
Journal of Software
关键词
动态电压调节
能量受限
低功耗
性能最优
软件预取
dynamic voltage scaling
energy-constrained
low power
performance optimization
software prefetching
