WearCore: A core for wearable workloads?

Sanyam Mehta, J. Torrellas
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引用次数: 5

Abstract

Lately, the industry has recognized immense potential in wearables (particularly, smartwatches) being an attractive alternative/supplement to the smartphone. To this end, there has been recent activity in making the smartwatch `self-sufficient' i.e. using it to make/receive calls, etc. independently of the phone. This marked shift in the way wearables will be used in future calls for changes in the core micro-architecture of smartwatch processors. In this work, we first identify ten key target applications for the smartwatch users that the processor must be able to quickly and efficiently execute. We show that seven of these workloads are inherently parallel, and are compute- and data-intensive. We therefore propose to use a multi-core processor with simple out-of-order cores (for compute performance) and augment them with a light-weight software-assisted hardware prefetcher (for memory performance). This simple core with the light-weight prefetcher, called WearCore, is 2.9× more energy-efficient and 2.8× more area-efficient over an in-order core. The improvements are similar with respect to an out-of-order core.
WearCore:可穿戴工作负载的核心?
最近,业界已经认识到可穿戴设备(尤其是智能手表)的巨大潜力,它是智能手机的一个有吸引力的替代品/补充。为此,最近出现了使智能手表“自给自足”的活动,即使用它独立于手机拨打/接听电话等。这种可穿戴设备在未来使用方式上的显著转变,要求改变智能手表处理器的核心微架构。在这项工作中,我们首先为智能手表用户确定了处理器必须能够快速有效地执行的十个关键目标应用程序。我们展示了这些工作负载中有七个本质上是并行的,并且是计算和数据密集型的。因此,我们建议使用具有简单乱序内核的多核处理器(用于计算性能),并使用轻量级软件辅助硬件预取器(用于内存性能)来增强它们。这个带有轻量级预取器的简单核心被称为WearCore,与按顺序的核心相比,能效提高2.9倍,面积效率提高2.8倍。对于乱序核,改进是类似的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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