Abstract: A system for generating a robustness score for hardware components, nodes, and clusters of nodes in a computing infrastructure is provided. The system includes a memory and at least one processing device coupled to the memory. The processing device is to obtain first telemetry data associated with a selected portion of a computing infrastructure, and the selected portion includes a first node and a first hardware component. The processing device is further to obtain first metadata associated with the selected portion, input one or more telemetry inputs corresponding to the first telemetry data into a machine learning model, input one or more metadata inputs corresponding to the first metadata into the machine learning model, and generate, from the machine learning model, a first robustness score for the first hardware component representing a health state of the first hardware component.

Abstract: A workload orchestrator in a disaggregated computing system manages Infrastructure Processing Units (IPUs) in a bidirectional way to provide redundancy and optimal resource configurations. Light-weight machine learning capabilities are used by the IPUs and the workload orchestrator to profile workloads, specify a redundancy level for each workload phase and predict a configuration that can provide optimal performance and security for the disaggregated computing system.

Abstract: This disclosure presents methods and devices that implement dynamic transmit power control techniques in terminal devices with multiple radio frequency (RF) transmitters and/or in a multi-terminal device environment to comply with regulatory RF exposure limits and standards while enhancing device performance. For example, the present disclosure provides a device including a processor configured to monitor a transmit power for each of a plurality of transmitters; determine a transmit power reduction to be applied to the plurality of transmitters based on a total simultaneous transmit power of the plurality of transmitters exceeding a threshold; define a respective amount of the transmit power reduction to be applied to each transmitter of the plurality of transmitters based on one or more parameters; and apply the respective amount of the transmit power reduction to each transmitter of the plurality of transmitters.

Abstract: A system for generating a robustness score for hardware components, nodes, and clusters of nodes in a computing infrastructure is provided. The system includes a memory and at least one processing device coupled to the memory. The processing device is to obtain first telemetry data associated with a selected portion of a computing infrastructure, and the selected portion includes a first node and a first hardware component. The processing device is further to obtain first metadata associated with the selected portion, input one or more telemetry inputs corresponding to the first telemetry data into a machine learning model, input one or more metadata inputs corresponding to the first metadata into the machine learning model, and generate, from the machine learning model, a first robustness score for the first hardware component representing a health state of the first hardware component.