节能计算:数据中心、移动设备和移动云

Massoud Pedram
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引用次数: 0

摘要

从仓库大小的数据中心到电池供电的移动设备再到移动云,能源消耗是电子系统设计的关键驱动因素。众所周知,能源效率最好通过特定于应用程序的节能硬件和运行时能源治理的组合来实现。节能硬件需要低功耗设备、单元库、电路和架构,而有效的能源治理需要重要的硬件和软件支持,例如实现动态功率/性能缩放、功率门控、核心整合和计算卸载。在我的演讲中,我将讨论三个示例问题,以说明可以采用的低功耗解决方案的范围以及可以实现的节能类型。这些问题是:(i)地理分布式云基础设施中的节能资源管理和作业调度,(ii)利用深度缩放设备的温度效应反演设计低功耗应用处理器,以及(iii)移动云计算环境中深度神经网络的节能计算卸载。我将以一系列最佳节能设计实践来结束我的演讲。
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Energy-Efficient Computing: Datacenters, Mobile Devices, and Mobile Clouds
Energy consumption is a key design driver for electronic systems ranging from warehouse-size datacenters to battery-powered mobile devices to mobile clouds. It is well known that energy efficiency is best achieved by an application-specific mix of power-efficient hardware and runtime energy governance. Power efficient hardware requires low power devices, cell libraries, circuits, and architectures whereas effective energy governance needs significant hardware and software support e.g., to achieve dynamic power/performance scaling, power gating, core consolidation, and computation offloading. In my talk I will discuss three example problems to illustrate the range of low power solutions that can be employed and the kind of power savings which are achievable. These problems are: (i) Power-efficient resource management and job scheduling in a geo-distributed cloud infrastructure, (ii) Design of low-power application processors exploiting the temperature effect inversion of deeply scaled devices, and (iii) Energy-efficient computation offloading for deep neural networks in a mobile cloud computing environment. I will conclude my talk with a list of best power-efficient design practices.
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A Dynamic Programming Technique for Energy-Efficient Multicore Systems Holistic Approaches to HPC Power and Workflow Management* IGSC 2018 PhD Workshop on Power/Energy Management at Extreme Scale [Copyright notice] DiRP: Distributed Intelligent Rendezvous Point for Multicast Control Plane
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