用流沙释放真正的效用计算

Zhenyuan Ruan, Shihang Li, Kaiyan Fan, M. Aguilera, A. Belay, S. Park, Malte Schwarzkopf
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引用次数: 2

摘要

今天的云是低效的:它们对cpu、gpu、内存和存储等资源的利用率很低。之所以会出现这种低效率,是因为应用程序以可变的速率和比例消耗资源,而云以固定的速率和比例提供资源。这种产品和消费风格的不匹配阻碍了效用计算愿景的充分实现。我们提倡可替换的应用程序,也就是说,应用程序可以独立地分发、扩展和迁移它们对不同资源的消耗,同时在不同的服务器上适配它们的可用性(例如,一台服务器上的内存,另一台服务器上的CPU)。我们的目标是充分利用资源,即使它们在服务器上暂时可用的时间只有几毫秒。我们正在开发一个名为Quicksand的框架,用于构建这样的应用程序,并释放效用计算的愿景。使用流沙实现DNN训练管道的初步结果是有希望的:流沙使机器之间不平衡或数量迅速变化的资源饱和。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unleashing True Utility Computing with Quicksand
Today's clouds are inefficient: their utilization of resources like CPUs, GPUs, memory, and storage is low. This inefficiency occurs because applications consume resources at variable rates and ratios, while clouds offer resources at fixed rates and ratios. This mismatch of offering and consumption styles prevents fully realizing the utility computing vision. We advocate for fungible applications, that is, applications that can distribute, scale, and migrate their consumption of different resources independently while fitting their availability across different servers (e.g., memory at one server, CPU at another). Our goal is to make use of resources even if they are transiently available on a server for only a few milliseconds. We are developing a framework called Quicksand for building such applications and unleashing the utility computing vision. Initial results using Quicksand to implement a DNN training pipeline are promising: Quicksand saturates resources that are imbalanced across machines or rapidly shift in quantity.
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