Constrained Power and Performance Optimization for Embedded Systems

嵌入式系统的受限功耗和性能优化

• 批准号: 0355071
• 负责人: Rajesh Gupta
• 金额: --
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-08-01 至 2007-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0355071&HistoricalAwards=false
• 关键词: Constrained; Power; Performance; Optimization; Embedded

Constrained Power and Performance Optimization for Embedded SystemsThe goal of this research is to explore techniques for power management ofembedded systems with provable bounds on power efficiency as well as adverseeffects on latency due to power management. The current state of the art insystem-level power management is limited to shutting parts of a system aftera certain period of idle time, thus ignoring the application timingconstraints, runtime traffic and application usage information. This workwill develop power-performance control "knobs" that will allow us to makeeffective online decisions. Specific applications will include power-awareresource scheduling in RTOS, timing-aware power optimizations and tradeoffsbetween power savings and application quality of service (e.g., misseddeadlines).Our technical focus is on solving two key problems: (a) latency-constrainedpower optimization, i.e., minimization of system-level power consumptionwith constrains on the effect of system latency due to power management; and(b) power-constrained performance optimization, e.g., system-level taskimplementation and scheduling within a given power budget. As a first step,we focus on analytic bounds on the effectiveness of online power managementalgorithms and their efficiency by developing bounds on latency increasesdue to power management. We introduce the notion of a competitive ratio asa quantitative measure of how well a given power management algorithmperforms against an optimum power consumption profile. Next, we incorporatethese analytic bounds in a broader system-level timing and power simulationengine which enables an accurate performance simulation while minimizing thedetails related to actual system functionality. Our experimental evaluationis through RTOS implementation of new power management services throughcoordinated scheduling and resource shutdown.

嵌入式系统的电源和性能优化的限制性和性能优化的目的是探索具有功率效率的可证明范围的电源管理技术以及由于电源管理而对延迟的不良效应。 当前的INSYSTEM级功率管理的当前状态仅限于在某些闲置时间时期关闭系统的一部分，因此忽略了应用程序的时间安排，运行时流量和应用程序使用情况信息。 这项工作将开发出功率绩效控制“旋钮”，这将使我们能够做出有效的在线决策。特定的应用程序将包括RTO中的Power-Awareresource计划，时光感知的功率优化和权衡之间的折衷和服务质量（例如，错过的DeadLines）。您的技术重点是解决两个关键问题：（a）延迟约束功率优化的功率优化，即最小化的系统 - 最小化的功能消耗效率效率效果效率效果效果效果效果效果效果效果效果效果效果效果效果效果效果效果效果效果效果效果效果效果; （b）功率受限的性能优化，例如，在给定的电力预算内的系统级任务实践和调度。作为第一步，我们通过在网上电源管理载体的有效性及其效率上关注分析界限，从而提高了对电力管理的潜伏期的界限。 我们介绍了竞争比率ASA定量量度的概念，以衡量给定功率管理算法对最佳功耗概况的效果。接下来，我们将分析界限纳入更广泛的系统级时序和功率仿真器中，从而可以进行准确的性能仿真，同时最大程度地减少与实际系统功能相关的theDetails。通过RTOS实施新的电力管理服务通过协调计划和资源关闭，我们的实验评估。