东南大学学报(英文版)
東南大學學報(英文版)
동남대학학보(영문판)
JOURNAL OF SOUTHEAST UNIVERSITY
2010年
3期
406-409
,共4页
动态电压调节%动态电源管理%电路功耗%电路延迟
動態電壓調節%動態電源管理%電路功耗%電路延遲
동태전압조절%동태전원관리%전로공모%전로연지
dynamic voltage scaling%dynamic power management%circuit power%circuit delay
基于电路功耗、电路延迟与工作电压之间的基本关系式,提出并证明了与DVS策略应用相关的4个定理.首先,针对单任务证明了最优工作电压的存在特性,即只需在一维电压的范畴内为单任务选择某个最优工作电压,且该电压所对应的任务结束时间必须与任务的截止期限保持一致.然后指出在同等条件下,DVS策略执行单任务所能达到的最小能耗必低于DPM 策略或者DVS 和DPM 结合策略所对应的最小能耗.最后,针对多任务组提出了能耗最小化定理,指出在满足所有任务截止期限的前提下,处理器能耗最小化的必要条件是处理器必须在整个任务段期间一直处于执行任务的状态.
基于電路功耗、電路延遲與工作電壓之間的基本關繫式,提齣併證明瞭與DVS策略應用相關的4箇定理.首先,針對單任務證明瞭最優工作電壓的存在特性,即隻需在一維電壓的範疇內為單任務選擇某箇最優工作電壓,且該電壓所對應的任務結束時間必鬚與任務的截止期限保持一緻.然後指齣在同等條件下,DVS策略執行單任務所能達到的最小能耗必低于DPM 策略或者DVS 和DPM 結閤策略所對應的最小能耗.最後,針對多任務組提齣瞭能耗最小化定理,指齣在滿足所有任務截止期限的前提下,處理器能耗最小化的必要條件是處理器必鬚在整箇任務段期間一直處于執行任務的狀態.
기우전로공모、전로연지여공작전압지간적기본관계식,제출병증명료여DVS책략응용상관적4개정리.수선,침대단임무증명료최우공작전압적존재특성,즉지수재일유전압적범주내위단임무선택모개최우공작전압,차해전압소대응적임무결속시간필수여임무적절지기한보지일치.연후지출재동등조건하,DVS책략집행단임무소능체도적최소능모필저우DPM 책략혹자DVS 화DPM 결합책략소대응적최소능모.최후,침대다임무조제출료능모최소화정리,지출재만족소유임무절지기한적전제하,처리기능모최소화적필요조건시처리기필수재정개임무단기간일직처우집행임무적상태.
Based on the fundamental relationship among the circuit power, the circuit delay and the supply voltage, four theorems associated with the application of dynamic voltage scaling (DVS) policies are proposed and proved. First, the existence characteristics of the optimal supply voltage for a single task are proved, which suggests that the optimal supply voltage for the single task should be selected only within a one-dimensional term, and the corresponding task end time by the optimal supply voltage should be identical with its deadline. Then, it is pointed out that the minimum energy consumption that the DVS policy can obtain when completing a single task is certainly lower than that of the dynamic power management (DPM) policy or the combined DVS+DPM policy under the same conditions. Finally, the theorem of energy consumption minimization for a multi-task group is proposed, which declares that it is necessary to keep the processor in the execution state during the whole task period to obtain the minimum energy consumption, while satisfying the deadline constraints of any task.