Method and system for offloading decoding of encoded data from a processing system

A non-transitory computer readable medium comprising computer readable program code, which when executed by a computer processor enables the computer processor to perform a method for managing information handling systems, the method comprising:

• obtaining, by a processing system and from an enhanced networking interface, encoded data associated with a video stream from a local data source,
• wherein the enhanced networking interface performs initial processing on the encoded data,
• wherein the initial processing comprises converting the video stream from an analog format to a digital format;
• wherein the encoded data is obtained from the enhanced networking interface via remote direct memory access (RDMA), and
• wherein the enhanced networking interface obtains the video stream from the local data source via the RDMA;
• performing, using decoding-dedicated hardware component of the processing system, a decoding of the encoded data to obtain decoded data;
• performing a computer vision (CV) inferencing on the decoded data to obtain inferencing data,
• wherein the inferencing is performed based on a federated CV regression model obtained from a CV manager operatively connected to the processing system via a network, and
• wherein the federated CV regression model is generated at least partially using a local CV regression generated by the processing system,
• wherein the local CV regression comprises a first set of weights, and
• wherein the federated CV regression comprises a second set of weights based on:
• the first set of weights,
• a third set of weights of a second local CV regression model generated by a second processing system, and
• a fourth set of weights associated with an initial federated CV regression model,
• wherein the initial federated CV regression model is generated based on a training of historical data provided to the processing system, and
• wherein the federated CV regression model is generated by applying an average of:
• the first set of weights,
• the second set of weights, and
• the fourth set of weights;
• providing the inferencing data to a processor;
• generating metadata corresponding to hardware of the local data source;
• and
• performing, by the processor, a remediation action based on the inferencing data and based on the metadata,
• wherein an operating system operates on the processor and not on the processing system, and
• wherein the remediation action comprises increasing a number of video cameras and a number of graphics processing units (GPUs) used by the local data source for CV inferencing.

A method for managing hardware resources, comprising:

• obtaining, by a processing system and from an enhanced networking interface, encoded data associated with a video stream from a local data source,
• wherein the enhanced networking interface performs initial processing on the encoded data,
• wherein the initial processing comprises converting the video stream from an analog format to a digital format;
• wherein the encoded data is obtained from the enhanced networking interface via remote direct memory access (RDMA), and
• wherein the enhanced networking interface obtains the video stream from the local data source via the RDMA;
• performing, using decoding-dedicated hardware component of the processing system, a decoding of the encoded data to obtain decoded data;
• performing a computer vision (CV) inferencing on the decoded data to obtain inferencing data,
• wherein the inferencing is performed based on a federated CV regression model obtained from a CV manager operatively connected to the processing system via a network, and
• wherein the federated CV regression model is generated at least partially using a local CV regression generated by the processing system,
• wherein the local CV regression comprises a first set of weights, and
• wherein the federated CV regression comprises a second set of weights based on:
• the first set of weights,
• a third set of weights of a second local CV regression model generated by a second processing system, and
• a fourth set of weights associated with an initial federated CV regression model,
• wherein the initial federated CV regression model is generated based on a training of historical data provided to the processing system, and
• wherein the federated CV regression model is generated by applying an average of:
• the first set of weights,
• the second set of weights, and
• the fourth set of weights associated with an initial federated CV regression model;
• providing the inferencing data to a processor;
• generating metadata corresponding to hardware of the local data source;
• and
• performing, by the processor, a remediation action based on the inferencing data and based on the metadata,
• wherein an operating system operates on the processor and not on the processing system, and
• wherein the remediation action comprises increasing a number of video cameras and a number of graphics processing units (GPUs) used by the local data source for CV inferencing.