Abstract: A platform includes a plurality of hardware blocks to provide respective functionality for use in execution of an application. A subset of the plurality of hardware blocks are deactivated and unavailable for use in the execution of the application at the start of the execution of the application. A hardware profile modification block of the platform identifies receives telemetry data generated by a set of sensors and dynamically activates at least a particular one of the subset of hardware blocks based on the physical characteristics, where following activation of the particular hardware block, the execution of the application continues and uses the particular hardware block.

Abstract: An apparatus of a computing node of a computing network, a method to be performed at the apparatus, one or more computer-readable storage media storing instructions to be implemented at the apparatus, and a system including the apparatus. The apparatus includes a processing circuitry to: receive, from an orchestration block, a first workload (WL) package including a WL and first computing resource (CR) metadata; recompose the first WL package into a second WL package that includes the WL and second CR metadata that is different from the first CR metadata, is based at least in part on CR information regarding a server architecture onto which the WL is to be deployed, and is further to indicate one or more processors of the server architecture onto which the WL is to be deployed; and send the second WL package to one or more processors of the server architecture for deployment of the WL thereon.

Abstract: In one embodiment, a method comprises determining whether an automation recommendation for a network is to be forwarded to a management system of the network, wherein the automation recommendation specifies an action to take with respect to a plurality of platforms of the network and is received from a recommendation system utilizing artificial intelligence to generate the automation recommendation; responsive to a determination to forward the automation recommendation, assessing an impact of the automation recommendation; and performing an action with respect to the automation recommendation based on the impact.

Abstract: Telemetry information in the form of platform telemetry, virtualization layer telemetry, and application telemetry can be used to estimate power consumption of a software entity, such as a virtual machine, container, application, or network slice. A controller can take various actions based on software entity power consumption information. If a power limit of an integrated circuit component is exceeded, the controller can reduce the power consumption of a software entity or move the software entity to another integrated circuit component to reduce the power consumption of the integrated circuit component. The controller can determine a total software entity power consumption for software entities associated with a user entity and take actions to keep the total software entity power consumption within a power budget.

Abstract: Techniques for reassembling fragmented datagrams are disclosed. Packets may be received and classified. Packets of a fragmented datagram may be stored for later reassembly. In the illustrative embodiment, a datagram is reassembled based on an identified class of service associated with the datagram. Additionally or alternatively, in the illustrative embodiment, a replay window of a replay attack detector may be tuned based on hardware performance of a compute device.

Abstract: A system comprising a first processor unit comprising a first register to store a metric for the first processor unit; and circuitry to initiate sharing of the metric with a second processor unit without the use of an inter-processor interrupt.

Abstract: Techniques for managing workloads in processor cores are disclosed. High priority or mission critical workloads may be assigned to processor cores of a processor. When a power limited throttling condition is met, the processor may throttle some of its cores while not throttling the cores with the high priority or mission critical workloads assigned to it. Such an approach can ensure that mission critical workloads continue even upon throttling of the processor cores.

Abstract: A performance monitor provides cache miss stall and memory bandwidth usage metric samples to a resource exhaustion detector. The detector can detect the presence of last-level cache and memory bandwidth exhaustion conditions based on the metric samples. If cache miss stalls and memory bandwidth usage are both trending up, the detector reports a memory bandwidth exhaustion condition to a resource controller. If cache miss stalls are trending up and memory bandwidth usage is trending down, the detector reports a last-level cache exhaustion condition to the resource controller. The resource controller can allocate additional last-level cache or memory bandwidth to the processor unit to remediate the resource exhaustion condition. If bandwidth-related metric samples indicate that a processor unit may be overloaded due to receiving high bandwidth traffic, the resource controller can take a traffic rebalancing remedial action.

Abstract: A system comprising an interface to access a network slice power consumption parameter for a network slice comprising a logical network between two endpoints through a plurality of physical computing platforms; and a controller comprising circuitry, the controller to specify operating parameters for a plurality of hardware resources of a first physical computing platform in accordance with the network slice power consumption parameter.

Abstract: In one embodiment, a computing device includes processing circuitry to receive a request to evaluate a plurality of platform configurations for deployment of an application workload on a compute platform, wherein the application workload is to be deployed based on one or more workload requirements; deploy a representative workload on the compute platform based on the plurality of platform configurations, wherein the representative workload is representative of the application workload; obtain performance data for the plurality of platform configurations, wherein the performance data is obtained based on deploying the representative workload on the compute platform; and determine, based on the performance data, whether the plurality of platform configurations satisfy the one or more workload requirements.

Abstract: Telemetry information provided by a computing device includes switching key performance indicators (KPIs), platform KPIs, and topology information. The telemetry information is used to identify performance issues at the computing device, such as packets being dropped in a virtual switching stack or misconfiguration errors. A virtual switching monitor can identify which layers in the switching stack have errors and whether the errors occur along a transmit or receive path in the switching stack. A virtual switching controller can identify remedial actions that can be taken at the computing device to remedy a performance issue. A remedial action can be taken automatically, subject to user approval, or automatically after additional criteria are met.