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Execution Traces of an MNIST Workflow on a Serverless Edge Testbed

<p>For the evaluation of a Serverless Edge Computing platform, we built an Edge Cloud testbed consisting of several machines:</p> <ul> <li>A Cloud VM</li> <li>An Nvidia Jetson TX</li> <li>Four Raspberry Pi 3b+</li> <li>Two Intel NUCs with i5 processors</li> </ul> <p>We were interested in profiling these devices with a Machine Learning workflow deployed as a serverless application. To that end, we implemented three functions: Preprocessing, Training, and Serving as OpenFaaS functions. The workflow trains an MNIST model.</p> <p>&nbsp;</p>

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
8
Engagement
4

Topics

Dataset details

Repository
zenodo
Published
January 26, 2020
License
cc-by-4.0
DOI
10.5281/zenodo.3628453
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