摘要:通过超参数优化自动部署正确的大小

Aniruddha Rakshit, Jayson G. Boubin
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引用次数: 0

摘要

物联网(IoT)和边缘部署是多种多样、复杂且高度受限的。这些性质使得先验地验证正确性变得困难或不可能。我们介绍了用于边缘和物联网部署的自动部署适当规模工具的早期工作。我们的工具使用威力测试平台来精确模拟候选部署形式因素,并优化部署参数以最小化成本。我们表明,我们的早期工作发现最优部署配置比贝叶斯优化快6.3倍,贝叶斯优化是最先进的超参数优化技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Poster Abstract: Automatic Deployment Right-Sizing Through Hyperparameter Optimization
Internet of Things (IoT) and Edge deployments are diverse, complex, and highly constrained. These properties make correctness difficult or impossible to verify a priori. We present early work on an automatic deployment right-sizing tool for edge and IoT deployments. Our tool uses the PROWESS testbed to accurately emulate candidate deployment form-factors, and optimizes deployment parameters to minimize costs. We show that our early work finds optimal deployment configurations 6.3X faster than Bayesian optimization, a state of the art hyperparameter optimization technique.
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