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Estimated monthly payment based on 36 month fair market lease.

Financing available through Hewlett-Packard International Bank plc (HPIB), Liffey Park Technology Campus, Barnhall, Leixlip, Co. Kildare, Ireland. Co. No. 289479 or other subsidiaries of Hewlett-Packard Financial Services ("HPFS") to qualified customers and is subject to credit approval and execution of standard HPIB/HPFS documentation. Rates and terms are based on customer's credit rating, offering types, services and/or equipment type and options. Not all customers may qualify, consumers specifically excluded. Not all services or offers are available in all countries. Other restrictions may apply. HPIB reserves the right to change or cancel this program at any time without notice.



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HPE Swarm Learning Software 20 Containers 1-year Subscription E-LTU



HPE Swarm Learning Software 10 Containers 1-year Subscription E-LTU



HPE Swarm Learning Software 5 Containers 1-year Subscription E-LTU



What's New

  • Fully-supported containerized software.
  • Three software SKU’s are available 5, 10 and 20 nodes with a 1-year subscription license.

Key Features

Preserve Privacy for Machine Learning

With HPE Swarm Learning, raw data is not transferred to a central location or between locations: source data stays at the data source.

The learnings are shared between participating nodes, preserving data privacy, and improving insights.

Decentralized Machine Learning

HPE Swarm Learning unlocks machine learning with features like global-state merge, without needing a centralized node for training.

Collaborative model training at edge devices.

Parameters are merged at the edge or data source.

Decentralized architecture increases reliability: there is no single point of failure.

Machine Learning at the Edge Where Data Resides

HPE Swarm Learning preserves network bandwidth, as learnings are at the data source.

Near or at data source enables prompt inferences.

Improved Efficiency for Model Training

In case of failure, HPE Swarm Learning allows the remaining nodes to continue machine learning. As the node comes up, it continues participation.

No back-and-forth transfer of data, saving bandwidth and data duplication.

Enables prompt inferences at the data source.

Linux is the registered trademark of Linus Torvalds in the U.S. and other countries. Red Hat is a registered trademark of Red Hat, Inc. in the United States and other countries. All third-party marks are property of their respective owners.

* Prices may vary based on local reseller.

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