Are you concerned about data privacy or regulations when moving data for your machine learning (ML)? Is your data distributed and preventing you from collaboration for improved insights where they are most needed? HPE Swarm Learning provides decentralized privacy-preserving, edge ML at the data source. The blockchain network provides the ability to collaboratively share the learnings of the models with participating HPE Swarm Learning nodes for insights at the data source, tremendously enhancing data privacy and improving insights.
HPE Swarm Learning extends federated learning and obviates the need for a central server. A decentralized, privacy-preserving ML framework utilizes the computing power at, or near, the distributed data sources to run the ML algorithms that train the models. Training the model occurs at the edge where data is most recent, where accurate, and data-driven decisions are necessary.
How do you enable a system to perform like a supercomputer, but run like a cloud?
HPE Cray System Management for HPE Cray supercomputers is a solution enabling system administrators to manage large-scale supercomputers leveraging the architecture and advances of hyper-scalers and cloud providers. While offering the familiar capabilities of high performance computing (HPC) system management software, HPE Cray System Management enables customers to go beyond the traditional and enable new services, deploy broad ranges of workloads, and drive towards the as-a-service experience. Built to manage systems scaling to Exascale, HPE Cray System Management offers everything needed for manageability, reliability, and interoperability for your HPE Cray supercomputers.
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