Changgang-Zheng/Planter

Planter is a modular framework for realising in one-click in-network machine learning algorithms.

19
/ 100
Experimental

Planter helps network engineers and researchers quickly deploy machine learning classification tasks directly within network data planes. You provide a configuration file and your dataset, and Planter automates the process of offloading the classification logic into the network infrastructure. This allows for faster, more efficient processing of network data by leveraging in-network computation.

No commits in the last 6 months.

Use this if you need to perform machine learning classification on data directly within your network's programmable data plane to improve processing speed and efficiency.

Not ideal if your machine learning tasks are not classification-based or if you do not have access to a programmable data plane in your network infrastructure.

network-engineering in-network-computing network-performance-optimization network-security-analytics data-plane-programming
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 8 / 25
Community 4 / 25

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Last pushed

Jun 13, 2024

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