A Scalable Cloud Based on Commodity Hardware

Saibal K. Ghosh, D. Agrawal
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Abstract

The recent explosion in the speed and connectivity of the Internet has opened up the possibility of millions and possibly billions of devices connected together. Combined with the development of small, low power devices, new paradigms in the field of computing have opened up. Traditional passive electronic devices now have rudimentary computing capabilities. The resulting Internet of Things (IoT), comprised of smart interconnected devices is improving our ability to gather ambient information and make informed decisions that directly benefit humanity. However, the ubiquity of these devices also presents an interesting scenario wherein the devices can perform limited general-purpose computations when they are not performing their primary functions. A computational task divided into a large number of smaller, micro tasks, each of which take only a few CPU cycles to complete. By distributing these tasks over a large number of devices, we can achieve a substantial amount of computation with seemingly modest devices. In this work, we explore a mechanism to enable such massively parallel computations in low powered commodity hardware devices through fine-grained task parallelism.
基于商用硬件的可扩展云
最近互联网的速度和连接性的爆炸式增长,使数百万甚至数十亿台设备连接在一起成为可能。随着小型、低功耗器件的发展,计算领域开辟了新的范式。传统的无源电子设备现在具有基本的计算能力。由此产生的由智能互联设备组成的物联网(IoT)正在提高我们收集环境信息并做出直接造福人类的明智决策的能力。然而,这些设备的普遍性也提出了一个有趣的场景,即设备在不执行其主要功能时可以执行有限的通用计算。一个计算任务被分成许多较小的微任务,每个任务只需要几个CPU周期来完成。通过将这些任务分配到大量的设备上,我们可以用看似不起眼的设备实现大量的计算。在这项工作中,我们探索了一种机制,通过细粒度的任务并行,在低功耗的商用硬件设备上实现这种大规模并行计算。
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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