Editor’s Note: HPE Swarm Learning product is now offered only as a community edition.

HPE Swarm Learning is a decentralized, privacy-preserving Machine Learning framework. This ML framework utilizes the computing power at, or near, the distributed data sources to run the Machine Learning algorithms that train the models. It uses the security of a blockchain platform to share learnings with peers in a safe and secure manner. In HPE Swarm Learning, training of the model occurs at the edge, where data is most recent, and where prompt, data-driven decisions are mostly necessary. In this completely decentralized architecture, only the insights learned are shared with the collaborating ML peers, not the raw data. This tremendously enhances data security and privacy.

Swarm Learning nodes works in collaboration with other Swarm Learning nodes in the network. It regularly shares its learnings with the other nodes and incorporates their insights. This process continues until the Swarm Learning nodes train the model to desired state. User can monitor the progress of the current training as shown in the below image. It shows all running Swarm nodes, loss, model metric (for example, accuracy) and overall training progress for each User ML node. On hovering over the "progress bar", one can see the number of completed epochs and the total number of epochs.

User can now extend Swarm client to support other machine learning platforms as well. Currently Swarm client supports machine learning platforms like PyTorch and Keras (based on Tensorflow 2 in backend). Please find the instructions to extend Swarm client here.

We are happy to announce Swarm 2.2.0 community release. In this release, we have delivered key enhancements on UI/UX, which includes experiment tracking for easier “birds-eye” visualization of past training rounds, parallel Swarm installation on multiple hosts, Podman support via SLM-UI etc., that will significantly enhance user experience. We have also added powerful features to Swarm manageability framework for better management of user ML workloads.

Articles

• 2021 Nature Paper - Swarm Learning for decentralized and confidential clinical machine learning
• Research gate - Swarm Learning as a privacy-preserving machine learning approach for disease classification

Learn more about HPE Swarm Learning and its underlying technology

- The big shift: What is swarm learning?

Swarm learning is the next gold rush for machine intelligence - training at the edge so the edge devices get smarter and also train their peers. With no central authority, Blockchain is integrated to add control, privacy, and security. Learn more by watching What is swarm learning?:

Listen to what the experts are saying

- How to optimize machine learning at the edge with HPE Swarm Learning

In this video Ronald van Loon and HPE Chief Technologist, Krishnaprasad Shastry, talk about optimizing machine learning at the edge with swarm learning. Learn more by watching How to optimize machine learning at the edge with HPE Swarm Learning:

Resources

• HPE Swarm Learning community edition
• Try HPE Swarm Learning examples
• HPE Swarm Learning client

Any questions on HPE Swarm Learning?

Join the HPE Developer Slack Workspace and start a discussion in our #hpe-swarm-learning channel.