XPS: EXPL: FP: Symbiotic Power Management for Integrated CPU - GPU Platforms

XPS：EXPL：FP：集成 CPU - GPU 平台的共生电源管理

• 批准号: 1438958
• 负责人: Sherief Reda
• 金额: $ 30万
• 依托单位: Brown University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1438958&HistoricalAwards=false
• 关键词: XPS; EXPL; FP; Symbiotic; Power

Power consumption is a major constraint on the operation of mobile computing devices. By reducing power consumption, it will be possible to prolong the operational time of battery operated devices. Modern computing devices integrate Central Processing Units (CPUs) and Graphic Processing Units (GPUs) on the same die to cater to the performance needs of various software applications. These software applications are usually written to execute parallel threads that make use of the CPUs and the GPUs. Integrated CPU-GPU devices offer many advantages over discrete CPU-GPU systems, including higher performance, reduced power consumption, and finer-grained interactions between the CPU and GPU.The overarching goal of this proposal is to explore a new paradigm for symbiotic power management that exploits the structure and semantics of parallel programming languages for CPU-GPU devices to deliver improved power management capabilities. To achieve this goal, the PI will first identify the operational phases of software applications directly from their parallel programming constructs, and then use the identified phases to devise an adaptive power management method that determines the optimal resources (e.g., frequency-voltage settings and number of cores) to meet performance targets while offering large reductions in power consumption. In synergy with the overarching goal, the PI will pursue an educational outreach program that includes: expanding on-going projects targeted for local high-school students to increase their knowledge of energy challenges in computing systems; developing courses on high-performance computing systems; involving undergraduate students in research experiences; and outreach to industry.

功耗是对移动计算设备运行的主要限制。通过减少功耗，可以延长电池操作设备的运行时间。现代计算设备集成了中央处理单元（CPU）和图形处理单元（GPU），以满足各种软件应用程序的性能需求。这些软件应用程序通常被编写为执行使用CPU和GPU的并行线程。 集成的CPU-GPU设备比离散的CPU-GPU系统具有许多优势，包括更高的性能，降低的功耗以及CPU和GPU之间的较细粒度的相互作用。该提案的总体目标是探索一个新的范式，以探索用于求解式电源的新型范式，以利用与CPU-GP的结构和SEMBALLAYD SEMBALSICS for SEMADINES for cpupu for cpupu for CPUPU进行了操作。为了实现这一目标，PI将直接从其并行编程结构中直接识别软件应用程序的运行阶段，然后使用确定的阶段来设计一种自适应功率管理方法，该方法确定最佳资源（例如，频率电压设置和核心数量），以满足绩效目标，同时提供大量降低动力消费。与总体目标协同作用，PI将遵循一个教育外展计划，其中包括：扩大针对当地高中生的持续项目，以增加对计算系统中能源挑战的了解；开发有关高性能计算系统的课程；让大学生参与研究经验；并向工业宣传。