An energy efficient platform for mobile computing

我们的移动的设备正在努力满足最终用户的期望和工程现实。这些设备的计算能力是由移动的应用程序的指数增长驱动的，以支持消费者的便利性、社交网络等环境、安全性和生产力。因此，移动的存储器带宽每两年翻一番，预计到2017年64 Gb/s移动的存储器带宽需求将远远超出行业标准存储器接口技术的预计容量。然而，电池技术和热预算的进步正在落后。根据目前的趋势和国际半导体技术路线图（ITRS）预测，到2024年，手持设备将消耗约7瓦的功率，而预计的热预算将限制为仅1瓦。总之，未来移动的计算的主要挑战是：较低的读写带宽、较高的延迟以及给定电池寿命的有限处理能力。这项研究计划正是基于这些挑战而提出的。移动的系统中的能量低效率主要源于设计用于支持最高容量或峰值性能的硬件的限制。然而，系统的最高容量仅在其操作时间的一小部分中被利用，并且大部分时间系统未被充分利用。虽然系统利用率不足，但现有硬件不允许相应地扩展能耗。本研究的目的是使能源效率高性能的移动的平台，将建立在几个关键的想法：1。可扩展的片上网络，支持高能效并行数据处理。2.一种智能资源管理，可以感知处理器负载，并相应地启用、关闭或改变内核的频率，以不同的速率进行计算。3.灵活、细粒度的动态电压和频率缩放方案，使资源管理器能够最大限度地提高能效。4.能量比例，高带宽存储器接口。我的研究的成功执行将塑造移动的处理器和内存路线图，以节能的方式满足未来移动的计算的需求。*

Our mobile devices are struggling to meet end-user expectation and engineering reality. Compute capability of these devices are driven by exponential growth in mobile apps to support consumer convenience, context such as social networking, security and productivity. As a result, the mobile memory bandwidth is doubling every two years, and predicted 64 Gb/s mobile memory bandwidth requirement by 2017 will be well beyond the projected capacity of industry standard memory interface technology. However, advance in battery technology and thermal budget is falling behind. Based on current trend and international technology road map for semiconductor (ITRS) projection, in 2024 a hand held device will dissipate approximately 7 Watts of power whereas the projected thermal budget sets the limit to be 1 watt only. To summarize, main challenges for future mobile computing are: lower read and write bandwidth, higher latency, and limited processing power for the given battery life. This research proposal is motivated by these challenges. Energy inefficiency in mobile systems is mainly originated from limitation of hardware which is designed to support the highest capacity or peak performance. However, highest capacity of the system is utilized for only a small fraction of its operating time, and most of the time the system is under-utilized. Although the system is under-utilized, the existing hardware does not allow energy consumption to scale accordingly. This research aims at enabling energy efficient high performance mobile platform that will be built upon several key ideas: 1. Scalable on-chip network that enables energy efficient parallel data processing. 2. An intelligent resource management that can sense processor load, and accordingly enable, shutdown or change frequency of the core to compute at a different rates. 3. Agile, fine grained dynamic voltage and frequency scaling schemes that enables the resource manager to maximize energy efficiency. 4. Energy proportional, high bandwidth memory interface. Successful execution of my research will shape mobile processor and memory road map that meets the demand for future mobile computing in an energy conscious manner.**********