Abstract: A method includes collecting data of states from a physical artifact at a first frequency using one or more data collection devices, wherein the states describe performance of the physical artifact in real-time, instantiating a first digital representation comprising a digital twin of the physical artifact, wherein the first digital representation mimics the physical artifact and a first state of the states, conducting an analysis to determine whether a first granularity of the collected data is sufficient based upon whether the first state falls within boundaries of operation that are expected for the digital twin, and adjusting a resolution at which the digital twin represents the physical artifact based upon the analysis to determine whether the first granularity of the collected data is sufficient.

Abstract: In an example implementation consistent with the features disclosed herein, a computer-implemented method includes monitoring power available to a plurality of nodes. Each node corresponding to an electronic component, device, or group of devices. The method includes detecting that the power available to the nodes is outside a power range within which all of the nodes can operate at a full operation level. When the power available to the node is outside the power range, allocation of the available power amongst the nodes is determined and at least some of the nodes are signaled to transition to a mode that utilizes less power.

Abstract: Systems and methods are provided for incorporating an optimized dispatcher with an FaaS infrastructure to permit and restrict access to resources. For example, the dispatcher may assign requests to “warm” resources and initiate a fault process if the resource is overloaded or a cache-miss is identified (e.g., by restarting or rebooting the resource). The warm instances or accelerators associated with the allocation size that are identified may be commensurate to the demand and help dynamically route requests to faster accelerators.

Abstract: Systems and methods are provided for incorporating an optimized dispatcher with an FaaS infrastructure to permit and restrict access to resources. For example, the dispatcher may assign requests to “warm” resources and initiate a fault process if the resource is overloaded or a cache-miss is identified (e.g., by restarting or rebooting the resource). The warm instances or accelerators associated with the allocation size that are identified may be commensurate to the demand and help dynamically route requests to faster accelerators.

Abstract: Systems and methods are provided for incorporating an optimized dispatcher with an FaaS infrastructure to permit and restrict access to resources. For example, the dispatcher may assign requests to “warm” resources and initiate a fault process if the resource is overloaded or a cache-miss is identified (e.g., by restarting or rebooting the resource). The warm instances or accelerators associated with the allocation size that are identified may be commensurate to the demand and help dynamically route requests to faster accelerators.

Abstract: Systems and methods are provided for incorporating an optimized dispatcher with an FaaS infrastructure to permit and restrict access to resources. For example, the dispatcher may assign requests to “warm” resources and initiate a fault process if the resource is overloaded or a cache-miss is identified (e.g., by restarting or rebooting the resource). The warm instances or accelerators associated with the allocation size that are identified may be commensurate to the demand and help dynamically route requests to faster accelerators.

Abstract: Systems and methods are provided for incorporating an optimized dispatcher with an FaaS infrastructure to permit and restrict access to resources. For example, the dispatcher may assign requests to “warm” resources and initiate a fault process if the resource is overloaded or a cache-miss is identified (e.g., by restarting or rebooting the resource). The warm instances or accelerators associated with the allocation size that are identified may be commensurate to the demand and help dynamically route requests to faster accelerators.

Abstract: Quantifying power usage for a service. An example method may include identifying a dependency model for the service, the dependency model based in part on infrastructure providing the service. The method may also include determining power usage for the service using the dependency model.

Abstract: The present disclosure includes a system and method for apportioning power consumption. In an example of apportioning power consumption according to the present disclosure, a transaction mix for a service is determined (104, 204, 330, 420), component resource usage for each of a number of components that are used while completing the service is determined (106, 206, 108, 208, 422), and component power consumption for each of the number of components is determined by use of the component resource usage (334, 424).

Abstract: According to an example, a method for area occupancy information extraction may include receiving a signal from a sensor, and determining a number of occupants moving within a first area based on the signal. The method may further include determining when an occupant is moving and a direction of motion of the occupant based on the signal, and determining a most likely trajectory based on the direction of motion of the occupant. The method may also include controlling, by a processor, a service in the first area based on the determination of the number of occupants, the determination of when the occupant is moving and the direction of motion of the occupant, and/or the determination of the most likely trajectory.

Abstract: Quantifying power usage for a service. An example method may include identifying a dependency model for the service, the dependency model based in part on infrastructure providing the service. The method may also include determining power usage for the service using the dependency model.

Abstract: Apparatuses associated with liquid coolant supply are disclosed. One example apparatus is a computing cartridge which includes a first electronic device and a liquid-cooled cold plate. The computing cartridge also includes a first thermal couple between the first electronic device and the cold plate. The computing cartridge also includes an inlet fluid connector. The inlet fluid connector may supply a liquid coolant to the cold plate. The computing cartridge also includes an outlet fluid connector. The outlet fluid connector may facilitate return of the coolant from the cold plate.

Abstract: Quantifying power usage for a service. An example method may include identifying a dependency model for the service, the dependency model based in part on infrastructure providing the service. The method may also include determining power usage for the service using the dependency model.

Abstract: A model is provided that produces predicted sensor data as a function of at least one input feature that includes an adjustable setting of a cooling infrastructure. The model is able to model a non-linear relationship between the predicted sensor data and the adjustable setting.

Abstract: Systems and methods for operating based on recovered waste heat are described. In one example, the method includes receiving recovered waste heat power and operating at least one system component of a recovered waste heat based computing device based on the recovered waste heat power, where the at least one system component is coupled to a non-volatile memory of the recovered waste heat based computing device. The method further includes preserving operational states of the at least one system component in the non-volatile memory based on a current power level associated with the recovered waste heat power.

Abstract: In an implementation, a method for managing airflow distribution through a plurality of adaptive vent tiles comprises accessing a model that correlates an environmental condition with a setting arrangement of the plurality of adaptive vent tiles and operational settings of a plurality of fluid moving devices. The method also includes calculating, through implementation of the model, a setting arrangement of the plurality of adaptive vent tiles that results in a substantially optimized metric subject to a set of constraints, wherein the setting arrangement of the plurality of adaptive vent tiles comprises an arrangement in which adaptive vent tiles in respective groups of adaptive vent tiles have substantially uniform opening levels with respect to each other.

Abstract: An example device in accordance with an aspect of the present disclosure includes a substrate that may be disposed in a housing. The substrate includes a sprayer to spray coolant.

Abstract: Examples described herein include heat dissipating apparatuses with phase change material. In some examples, a heat dissipating apparatus comprises a wick structure to carry a cooling fluid to cool an electronic heat source, a vapor region to carry heated cooling fluid away from the wick structure, and a compartmentalized space separate from the vapor region comprising a phase change material to absorb energy from the heated cooling fluid.

Abstract: An example device in accordance with an aspect of the present disclosure includes a characterization engine and an allocation engine. The characterization engine is to receive information and characterizes expected temperature exposure of a memory device, to store a characterization profile of a plurality of memory devices of a computing system. The characterization engine is to refer to the characterization profile to identify the expected temperature exposure for a given memory device.

Abstract: In a method for generating a capacity schedule for a facility to meet a predefined operational goal, in which the facility is to receive resources from a first resource supply, a prediction of a supply of resources available from the first resource supply for a predetermined period of time is accessed. In addition, a prediction of a demand for resources in the facility during the predetermined period of time is accessed. The prediction of the supply of resources and the prediction of the demand for resources are inputted into a constrained optimization problem and the capacity schedule for the facility is generated by finding a solution to the constrained optimization problem.