Dell Products Inc.

Other

Emc IP Holding Company LLC

Dell & Products L.p.

Dharmesh M Patel

Ravikanth Chaganti

Rizwan Ali

Lucas A Wilson

John Kelly

Manpreet Singh Sokhi

Prem Pradeep Motgi

Ian Gerard Roche

Philip E Hummel

John A Lockman, Iii

Dan Kerning

Balasubramanian Chandrasekaran

Arvind Ramakrishnan Palamadai

Farzad Khosrowpour

Jenwei Hsieh

Daniel Kerning

Nicholas Chase Busick

Philip Hummel

Ian Roche

Yogesh Prabhakar Kulkarni

Mahmoud B Ahmadian

Ke Xu

Javier A Ponce

Ravikanth Changanti

William Brad Langford

Nicholas C Busick

Methods and systems for managing requests for functionalities of a data repository are disclosed. The data repository may store sensitive data (e.g., personal data), and may offer functionality (e.g., data access) in order to facilitate computer-implemented services. To prevent unauthorized access to and/or use of the sensitive data, an access control system may be implemented. For example, in order to gain access to data stored in the data repository, the access control system may prompt a requesting user to provide responses to security questions during authentication. The security questions may be based on details of personal experiences of the authorized user (e.g., identified from the personal data of the authorized user) and may be updated automatically when new data is introduced to the data repository. Therefore, the responses to the security questions required for authentication may be memorable to the authorized user and/or difficult to predict for unauthorized users.

Multifactor authentication based on user experiences

Methods, systems, and devices for managing operation of a data processing system that provides computer implemented services are disclosed. To do so, a request to perform a workload may be obtained. A type of the workload may be identified based on the request, and based on this type, computing resources required for performance of the workload may be identified. Potential locations for the performance of the workload may be filtered based on the required computing resources to identify a portion of the potential locations. Based on associations between types of workloads and sets of network characteristics, a set of network characteristics may be identified for the type. Based on the set of network characteristics, the potential locations may be further filtered to identify a sub-portion of the potential locations. Based on this identification, performance of the workload by at least one data processing system of the sub-portion may be initiated.

End to end drift detection in large scalable networks

A method for managing hardware resources comprises obtaining, by a computer vision (CV) manager, a request for a federated CV regression model, in response to the request: performing an initial training of the federated CV regression model using an initial training dataset to obtain an initial federated CV regression model, sending training requests to two local hardware resource systems, wherein each local hardware resource system implements a local camera system and a processing system, and wherein the training request comprises training a local CV regression model based on the processing system and the local camera system, obtaining the first local CV regression model and the second local CV regression model, generating the federated CV regression model using the two local CV regression models, and distributing the federated CV regression model to the first local hardware resource system and the second local hardware resource system.

Method and system for managing a federated computer vision regression model using distributed training

Methods and systems for managing collection of diagnostic data are disclosed. To collect diagnostic data, unmanaged devices may be used. The unmanaged devices may be registered with a data management system. During the registration process, procedures for processing diagnostic data from the unmanaged devices may be established. The procedures may be established based on data collection performance of the unmanaged devices. The procedures may reduce the likelihood of use of diagnostic data that is unreliable. Once obtained, the diagnostic data may be rated for different uses based on the performance of the hardware used to obtain the diagnostic data. Access controls for the diagnostic data may be put in place to manage distribution of the diagnostic data.

System and method for access control to and management of diagnostic data

Methods and systems for managing access and control of data are disclosed. To manage access and control, data management system may require registration and verification of devices associated with an individual or other individuals to which control over access may be granted. Data management system may vest control over access to data to the device associated with the individual for which data is stored, and progressively vest control over access to data to other devices associated with other individuals as an increasing amount of information indicating the lack of capacity of the individual to authorize access to data. When access to data is granted by the individuals, the data may be scrutinized with respect to other types of restrictions on distribution of the data.

System and method for managing access control of data across a distributed system

Methods and systems for managing collection of diagnostic data are disclosed. To collect diagnostic data, unmanaged devices may be used. The unmanaged devices may be registered with a data management system. During the registration process, procedures for processing diagnostic data from the unmanaged devices may be established. The procedures may be established based on data collection performance of the unmanaged devices. The procedures may reduce the likelihood of use of diagnostic data that is unreliable. Once obtained, the diagnostic data may be rated for different uses based on the performance of the hardware used to obtain the diagnostic data.

System and method for use based management of diagnostic data

Techniques described herein relate to a method for allocating graphics processing unit partitions for a computer vision environment. The method includes obtaining, by a computer vision (CV) manager, an initial graphics processing unit (GPU) partition allocation request associated with a CV workload; in response to obtaining the initial GPU partition allocation request: obtaining CV workload information associated with the CV workload; obtaining first CV environment configuration information associated with the GPU partition allocation request; generating an optimal GPU partition allocation based on the first CV environment configuration information and the CV workload information using a GPU partition model; and initiating performance of the CV workload in a CV environment based on the optimal GPU partition allocation.

Method and system for allocating graphics processing unit partitions for a computer vision environment

Methods and systems for managing the operation of a deployment are provided. The deployment may be managed in accordance with a subscription model. The subscription model may use subscriptions to define the extent and limits on use of services provided by the deployment. The subscription services and limits may be enforced by management controllers of network devices of the deployment. The management controllers may operate independently from control planes and data planes of the network devices. If a plane is suspected of being compromised, the management controllers may take action to confirm the suspicions. Test may be performed, and measurements may be taken to confirm whether a plane is compromised. If confirmed, then remedial activity may be initiated to address the compromised plane.

Service level verification in distributed system

A method for managing specialized hardware resources includes obtaining, by a resource partitioning agent, a request for a specialized workload, in response to the request: obtaining aggregation capability information corresponding to the specialized hardware resources in an information handling system, obtaining partitioning capability information associated with the specialized hardware resources, and initiating allocation of a set of specialized hardware resources to the specialized workload based on the aggregation capability information and the partitioning capability information.

System and method for allocation of a specialized workload based on aggregation and partitioning information

Methods and systems for managing storage of data in a set of storage tiers are disclosed. To manage storage of data, data management system may analyze data to identify topic classifications and topic rankings for the data. Data management system may prioritize storage of data in higher performing storage tiers based on the relevancy of the data for one or more purposes with respect to an individual. To identify relevant data with respect to the individual for which data is being stored, data management system may analyze data, including audio recordings of interactions between the individual and other individuals to identify topics relevant to the individual. Based on the identified topics, data management system may establish a relevancy quantification for the portions of data and use the relevancy quantification to select a storage tier in which to store the portion of the data.

System and method for managing storage of data in a set of storage tiers

Methods and systems for managing access to data in a data management system are disclosed. To manage access to data, data management system may limit the access to data stored within the data management system based on an identity of a requestor from which a request for a portion of the data is obtained. Data management system may identify an access control model usable to manage access to the data stored in the data management system based on topics associated with the identity of the requestor and relevancy of each topic. To identify an access control model, data management system may use the identity of the requestor to identify associated topics and topic rankings for the identified topics. Based on the identified access control model, data management may provide a response to the requestor to service the request for a portion of data.

System and method for managing access to data stored in a data management system

Methods and systems for performing workloads are disclosed. The workloads may be distributed across any number of processing elements for performance. The processing elements may be supported by communication elements. The operation of the communication elements may impact the rate at which the processing elements are able to complete the workloads. The operation of the communication elements may be dynamically configured to speed completion of workloads.

System and method for scheduling resources of distributed systems to perform workloads

A method for managing a virtual desktop infrastructure (VDI) environment includes: obtaining a plurality of target resource specific pool specific configuration templates for a target resource, in which each of the plurality of target resource specific pool specific configuration templates is associated with one or a plurality of virtual desktop (VD) pools, in which the target resource is a central processing unit (CPU); obtaining a common configuration template set; generating a VD pool configuration for each of the plurality of VD pools using the plurality of target resource specific pool specific configuration templates and the common configuration template set to obtain a plurality of VD pool configurations; selecting a default VD pool from the plurality of VD pools; and deploying, based on the selection, a plurality of VDs into the default VD pool using a VD pool configuration associated with the default VD pool.

Method and system for a common-attribute virtual desktop infrastructure (VDI) environment with tiered central processing unit (CPU) capabilities

A method for managing a VDI environment includes: obtaining a plurality of target resource specific pool specific configuration templates for a target resource, in which each of the plurality of target resource specific pool specific configuration templates is associated with one or a plurality of VD pools, in which the target resource is a GPU; obtaining a common configuration template set; generating a VD pool configuration for each of the plurality of VD pools using the plurality of target resource specific pool specific configuration templates and the common configuration template set to obtain a plurality of VD pool configurations; selecting a default VD pool from the plurality of VD pools; and deploying, based on the selection, a plurality of VDs into the default VD pool using a VD pool configuration associated with the default VD pool.

Method and system for a common-attribute virtual desktop infrastructure (VDI) environment with tiered graphics processing unit (GPU) capabilities

A method for managing selection of an inferencing workload placement based on security considerations includes obtaining, by a variant selection agent of a workload placement service and from a front-end device, a request for an inferencing payload associated with an inferencing workload implementing a generative artificial intelligence (AI) model, and in response to the request: performing a payload classification on the request to determine a variant selection for the inferencing workload, making a determination that the variant selection is a secured variant, in response to the determination, transmitting the request to the secured variant, wherein the secured variant executes an instance of the inferencing workload on a secured production environment, obtaining, from the secured variant, the inferencing payload, and providing the inferencing payload to the front-end device.

Growing community of inventors

Round Rock, TX, United States of America

Dharmesh M Patel