Collaborative Research: Eliminating the Energy Efficiency Barrier of Reconfigurable Architectures for Diverse Signal Processing in Mobile Devices

合作研究：消除移动设备中多样化信号处理的可重构架构的能效障碍

• 批准号: 1201834
• 负责人: Russell Tessier
• 金额: $ 26.5万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-06-01 至 2016-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1201834&HistoricalAwards=false
• 关键词: Collaborative; Research; Eliminating; Energy; Efficiency

Objective: The objective of this program is to cohesively use coarse-grained reconfigurable devices and highly-scalable non-volatile memory technologies to fundamentally improve energy efficiency in future mobile devices. The new device architecture provides the capability to dynamically exploit significant run-time computational workload variation and large algorithm design freedom inherent in most signal processing tasks, effectively enabling just-enough computation. The approach embraces the memory-intensive and time-varying nature of many signal processing tasks, which can be leveraged to reduce overall system energy consumption. In addition, these approaches make it feasible to apply aggressive run-time power management on reconfigurable architectures to minimize static energy consumption. To fully evaluate the potential of these new opportunities, a comprehensive design methodology including circuits, architectures, compiler, and run-time system is used. Intellectual Merit: The intellectual merit of this research lies in the cohesive integration and use of a coarse-grained reconfigurable device which includes interfaces to high-density non-volatile memory technology. This interface is exploited at the system level to dynamically adapt computation-intensive signal processing applications for significant energy savings. Broader Impacts: The broader impacts of this project are: 1) enhancement to graduate curricula in embedded systems and integrated circuit design, 2) application of the new technologies in the NSF-sponsored Engineering Research Center for Collaborative and Adaptive Sensing of the Atmosphere (CASA), 3) research infrastructure dissemination for education and training, and 4) outreach to high school students. The proposed architecture will enable future mobile devices to continue to track their historic performance and functionality scaling by supporting energy efficiency.

目标：该计划的目标是结合使用粗粒度可重构设备和高度可扩展的非易失性存储器技术，从根本上提高未来移动设备的能源效率。新的设备架构提供了动态利用大多数信号处理任务中固有的显着运行时计算工作负载变化和大算法设计自由度的能力，从而有效地实现了足够的计算。该方法涵盖了许多信号处理任务的内存密集型和时变特性，可用于降低总体系统能耗。此外，这些方法使得在可重构架构上应用积极的运行时电源管理以最小化静态能耗成为可能。为了充分评估这些新机会的潜力，需要使用包括电路、架构、编译器和运行时系统在内的综合设计方法。智力优点：这项研究的智力优点在于粗粒度可重构设备的紧密集成和使用，其中包括高密度非易失性存储器技术的接口。该接口在系统级被利用来动态调整计算密集型信号处理应用程序，从而显着节省能源。更广泛的影响：该项目的更广泛影响是：1) 增强嵌入式系统和集成电路设计方面的研究生课程，2) 在 NSF 资助的协作和自适应大气感知工程研究中心 (CASA) 中应用新技术），3）传播教育和培训研究基础设施，以及 4）向高中生推广。所提出的架构将使未来的移动设备能够通过支持能源效率来继续跟踪其历史性能和功能扩展。