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公开(公告)号:US20220417215A1
公开(公告)日:2022-12-29
申请号:US17845428
申请日:2022-06-21
Applicant: Nvidia Corporation
Inventor: Anand Parthasarathi , Binu Ramakrishnan , Joji Mekkattuparamban , Phil Rogers , Rajat Chopra , Satish Salagame
IPC: H04L9/40
Abstract: Systems and methods include a cloud-hosted management plane where an authenticated user can initiate a request to establish a remote session to an edge device. A request may be transmitted to create a secure tunnel between the edge device and the cloud-based management plane. The edge device may receive and use a set of credentials to trigger a web-socket tunnel from the edge device to the cloud-hosted management plane. This connection may be used for management of an edge device(s), troubleshooting edge inferencing, access/use of edge applications, and various other applications.
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公开(公告)号:US20240070277A1
公开(公告)日:2024-02-29
申请号:US18064480
申请日:2022-12-12
Applicant: NVIDIA Corporation
Inventor: Li Ge , Nivedita Viswanath , Philip Rogers , Rajat Chopra , Satish Salagame
CPC classification number: G06F21/57 , G06F21/602
Abstract: In various examples, systems for performing cloud-based updating of operating systems (e.g., root file systems) using system partitioning. For instance, a system(s) may initiate updates of the operating systems of machines, where the machines use system partitioning for the updating. More specifically, the system(s) may cause a machine to update the operating system using a standby system partition while the machine is currently running on another, active system partition. In some circumstances, the system(s) may perform these processes in order to update a cluster of machines, such as during a specific time period or at a certain frequency. By using such processes, the cluster of machines may still operate during the updating of the machines and/or even if the update fails on one or more of the machines.
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公开(公告)号:US20210117859A1
公开(公告)日:2021-04-22
申请号:US17015318
申请日:2020-09-09
Applicant: Nvidia Corporation
Inventor: Philip J. Rogers , Bhanu Pisupati , Tushar Khinvasara , Rajat Chopra , Kaustubh Purandare
Abstract: Resources, such as machine learning models, can be updated for an application without any significant downtime for that application. For an application hosted at a network edge, the application can be deployed in a container and one or more model versions stored in local storage at the edge, which can be mounted into the container as necessary. When a different model version is to be used, a configuration change or new context can be used to trigger the application to automatically change to the different model version. This updating can be performed seamlessly, without any loss of data.
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