Collaborative Research: Algorithmic Support for Power Aware Computing and Communication
Collaborative Research: Algorithmic Support for Power Aware Computing and Communication
批准号:
0514058
负责人:
Kirk Pruhs
金额:
$15.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-07-15 至 2009-06-30
中文摘要
智能优势:计算设备的功耗率呈指数级增长。这使得为设备提供能量和冷却这些设备变得越来越困难。功率感知计算在由小型电池供电节点组成的传感器网络领域尤为重要。传感器网络中的电源管理被认为是非常关键的,必须在协议栈的所有层进行处理。许多电源管理技术已经被提出和实现。这些技术中的大多数都是相似的,因为它们减少或消除了设备的某些或所有组件的功率。然而,在电源管理和性能之间存在着内在的冲突;一般来说,可用的功率越多,可以实现的性能就越好。因此,通常建议在性能不太关键的时候优先应用功耗降低技术。但是,这需要一个策略来确定在任何给定时间性能有多重要,以及如何应用特定的功耗降低技术。例如,要使用频率缩放技术,其中时钟的速度是动态变化的,需要一个策略来设置每个时间点的速度。越来越多的人认为,这些策略必须包含应用程序和高级操作系统提供的信息,而当前的电源管理工具和机制是不够的,需要更多的研究。作者建议将电源管理问题形式化为优化问题,然后根据这些标准开发最优算法。本研究的目标是为电源管理领域内的特定问题开发有效的算法,以及为能量有界和温度有界计算中出现的问题建立广泛适用的算法方法工具包。作者建议首先关注处理速度缩放和断电技术的问题,因为这些是目前在实践中占主导地位的技术。更广泛的影响:作者建议发展基础理论技术,并将这些技术应用于计算机系统中及时和重要的应用程序。两个pi都与应用领域的研究人员密切合作,以确保开发的理论模型与相关的现实问题相匹配。这是理论结果产生影响的必要条件。这项工作将继续促进这些实验系统研究人员和理论计算机科学之间非常富有成效的交叉受精。这项资助下的学生将受到这种研究理念的影响。他们将接受培训,积极主动地与应用领域的研究人员合作,将重要和有趣的问题带入理论界。他们还将被鼓励在系统和理论会议上发表结果工作,以确保新的算法发现产生影响。作为该项目的一部分,作者还计划继续向高中生推广工作,鼓励代表性不足的群体选择技术相关领域的职业。他们编写了一份报告,概述了计算机科学领域的各种机会,并计划让研究生和本科生在当地高中发表这份报告。该提案中的工作在演讲中有重点介绍。此外,他们计划让来自代表性不足群体的学生参与与电源管理相关的研究项目。
英文摘要
Intellectual Merit: The power consumption rate of computing devices has been increasing exponentially. This makes it increasingly difficult to supply energy to devices and to cool these devices. Poweraware computation is especially important in the domain of sensor networks which are composed of small battery-powered nodes. Power management in sensor networks is viewed as so critical that it must be dealt with at all layers of the protocol stack.Many power management techniques have been proposed and implemented. Most of these techniques are similar in that they reduce or eliminate power to some or all components of the device. However, there is an inherent conflict between power management and performance; in general, the more power that is available, the better the performance that can be achieved. As a result, it is generally proposed that power reduction techniques be preferentially applied during times when performance is lesscritical. However, this requires a policy to determine how essential performance is at any given time and how to apply a particular power reduction technique. For example, to use the frequency scaling technique, where the speed of the clock is changed dynamically, one needs a policy to set the speed at each point in time. There is a growing consensus that these policies must incorporate information provided by applications and high levels of the operating system, and that current tools and mechanisms for power management are inadequate and require more research. The authors propose to formalize powermanagement problems as optimization problems, and then develop algorithms that are optimal by these criteria. The goal of this research is to develop effective algorithms for specific problems within the domain of power management, as well as to build a toolkit of widely applicable algorithmic methods for problems that arise in energy-bounded and temperature-bounded computation. The authors propose to initially focus on problems that deal with speed scaling and power-down techniques, since these are currently the dominant techniques in practice.Broader Impacts: The authors propose to both develop fundamental theoretical techniques, and to apply these techniques to attack timely and important applications in computer systems. Both PIs have an established track record of working closely with researchers in applied areas to ensure that the theoretical models developed match the associated real-world problems. This is essential for theoretical results to have an impact. This work will continue to foster this very productive cross-fertilization betweenthese experimental systems researchers and theoretical computer science. The students supported under this grant will be influenced by this philosophy of research. They will be trained to be proactive in working with researchers in applied domains to bring important and interesting problems into the theory community. They will also be encouraged to publish the resulting work in systems as well as theory conferences to ensure that new algorithmic discoveries have an impact. As part of this project, the authors also plan to continue outreach work to high schools students, encouraging underrepresented groups to choose careers in technology related fields. They have developed a talk outlining diverse opportunities within computer science and plan to involve graduate and undergraduate students in presenting this talk at local high schools. The work in this proposal is featured in the talk. In addition, they plan to involve students from underrepresented groups in research projects related to power management.
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批准号:2209654
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资助金额:$25.08万
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AF: Small: Algorithmic Energy Management in New Information Technologies
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批准号:1421508
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项目类别:Standard Grant
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资助金额:$39.96万
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财政年份:2014
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负责人:Kirk Pruhs
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依托单位:
EAGER: A Framework for joint optimization of power management and performance in virtualized, heterogeneous cloud computing environments
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批准号:1253218
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财政年份:2012
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依托单位:
AF: Small: Green Computing Algorithmics
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批准号:1115575
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项目类别:Standard Grant
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资助金额:$34.99万
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财政年份:2011
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负责人:Kirk Pruhs
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依托单位:
Science of Power Management
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批准号:0936386
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项目类别:Standard Grant
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资助金额:$0.0万
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财政年份:2009
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负责人:Kirk Pruhs
-
依托单位:
Algorithmic Support for Power Management
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批准号:0830558
-
项目类别:Continuing Grant
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资助金额:$29.99万
-
财政年份:2008
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负责人:Kirk Pruhs
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依托单位:
Algorithmic Support for Temperature Aware Computing and Networking
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批准号:0448196
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项目类别:Standard Grant
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资助金额:$0.0万
-
财政年份:2004
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负责人:Kirk Pruhs
-
依托单位:
Collaborative Research: Algorithmic Problems in Next Generation Networks
-
批准号:0098752
-
项目类别:Standard Grant
-
资助金额:$22.99万
-
财政年份:2001
-
负责人:Kirk Pruhs
-
依托单位:
Online Network Optimization
-
批准号:9209283
-
项目类别:Continuing Grant
-
资助金额:$7.27万
-
财政年份:1992
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负责人:Kirk Pruhs
-
依托单位:
国内基金
海外基金
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