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A generic energy optimization framework for heterogeneous platforms using scaling models

机译:使用缩放模型的异构平台的通用能源优化框架

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Mobile platforms are becoming highly heterogeneous by combining a powerful multiprocessor system-on a-chip (MpSoC) with numerous other resources, including display, memory, power management IC, battery and wireless modems into a compact package. Furthermore, the MpSoC itself is a heterogeneous resource that integrates many processing elements such as CPU cores, GPU, video, image, and audio processors. Platform energy consumption and responsiveness are two major considerations for mobile systems, since they determine the battery life and user satisfaction, respectively. As a result, energy minimization approaches targeting mobile computing need to consider the platform at various levels of granularity. In this paper, we first present power consumption, response time, and energy consumption models for mobile platforms. Using these models, we optimize the energy consumption of baseline platforms under power, response time, and thermal constraints with and without introducing new resources. Finally, we validate the proposed framework through experiments on Qualcomm's Snapdragon 800 Mobile Development Platforms. (C) 2015 Elsevier B.V. All rights reserved.
机译:通过将功能强大的多处理器单芯片系统(MpSoC)与众多其他资源(包括显示器,内存,电源管理IC,电池和无线调制解调器)组合到紧凑的封装中,移动平台变得高度异构。此外,MpSoC本身是一种异构资源,它集成了许多处理元素,例如CPU内核,GPU,视频,图像和音频处理器。平台能耗和响应能力是移动系统的两个主要考虑因素,因为它们分别决定电池寿命和用户满意度。结果,针对移动计算的能量最小化方法需要考虑各种粒度级别的平台。在本文中,我们首先介绍了移动平台的功耗,响应时间和能耗模型。使用这些模型,我们可以在引入,不引入新资源的情况下,在功率,响应时间和热约束下优化基准平台的能耗。最后,我们通过在高通公司的Snapdragon 800移动开发平台上进行的实验来验证所提出的框架。 (C)2015 Elsevier B.V.保留所有权利。

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