在开放卷云上运行交互式感知应用程序

Qian Zhu, N. Yigitbasi, P. Pillai
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引用次数: 1

摘要

交互式感知应用,如手势识别和基于视觉的用户界面,使用计算密集型计算机视觉和机器学习算法处理高数据速率流。然而,它们需要极低的延迟来保持交互性并确保及时向用户提供结果。集群计算资源(如开放卷云部署提供的资源)可以帮助解决计算需求,但在实践中存在重大挑战。本文重点介绍了我们在并行化交互式感知应用程序、优化它们以获得最佳保真度和延迟以及在集群平台上放置、调度和执行它们方面所做的努力。我们还将研究尚未解决的问题和潜在的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Running Interactive Perception Applications on Open Cirrus
Interactive perception applications, such as gesture recognition and vision-based user interfaces, process high-data rate streams with compute intensive computer vision and machine learning algorithms. Yet, they require extremely low latencies to remain interactive and ensure timely results to users. Cluster computing resources, such as those provided by Open Cirrus deployments, can help address the computation requirements, but significant challenges exist in practice. This paper highlights our efforts to parallelize interactive perception applications, tune them for best fidelity and latency, and place, schedule, and execute them on a cluster platform. We also look at remaining open problems and potential solutions.
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