Abstract: Systems and methods disclosed herein can be used to provide power for a non-powered rack chassis. An enclosure shaped to fit within the non-powered rack chassis may be associated with or may include a power shelf. The power shelf may have at least one busbar to distribute the power from the power shelf to one or more sleds of the non-powered rack chassis.

Abstract: Systems and methods are directed to a leak detection system that incorporates non-contact sensors to detect leaks. The leak detection system may include local power supplies that may provide operational power to the non-contact sensors when remaining components, such as those associated with racks or electronic systems, are shipped, stored, or otherwise not provided with an external power supply. Low-powered non-contact sensors may particularly target small viewing areas for leak detection.

Abstract: Systems and methods disclosed herein can be used to supply power in a computing environment that may include a rack, multiple sleds, and a power-sharing logic. The rack may include a busbar, an alternating current (AC) input, and a plurality of rack power supply units (PSUs). The multiple sleds may include individual sled PSUs and power distribution board (PDBs). The power-sharing logic may be associated with the sled PSUs and the PDBs to allow sharing of power between the sled PSUs and through the PDBs.

Abstract: Systems and methods are directed toward multi-layer tubular arrangements that include a flow restrictive material between a first layer and a second layer. The first layer may be associated with a flow bore and may be surrounded, at least partially, by a flow restrictive material. The flow restrictive material may also be surrounding by a second layer. If an opening or hole forms in either the first or second layers, the flow restrictive material may block fluid ingress/egress to maintain operation of the multi-layer tubular until maintenance or repairs can be scheduled.

Abstract: Methods are described herein for manufacturing multi-component objects using artificial intelligence. The present invention may be directed to a method that includes determining an actual value of a first attribute of a first component of an object and determining, using a machine learning model and based on the actual value of the first attribute, an optimized value for a second attribute of a second component that is functionally interrelated to the first component in the object. The method may include selecting, from a plurality of second components each having a value for the second attribute within a tolerance range, a second component having the optimized value for the second attribute. The method may further include manufacturing the object using the first component and the selected second component.

Abstract: Approaches presented herein provide for active noise cancelation for individual components in an environment such as a data center. There can be various heat-generating components in a data center, as may include servers, processors, and network switches, that also result in the generation of excess noise, such as may be produced by fans used to remove heat from these components. An exhaust tubing can be used to direct a flow of heated air, directed by a fan, from an opening in a sound-proof housing to an outlet of the tubing. A microphone can be placed inside the exhaust tubing to record the waveform of the noise emitted by the fan that is directed into the exhaust tubing. An inverted phase waveform can be generated and provided for playback by a speaker in the exhaust tubing. The inverted phase waveform will combine with the emitted waveform and, through destructive interference, largely cancel out the emitted waveform.

Abstract: Some embodiments described herein provide intelligent movable racks for a data center and a central system for monitoring and directing the positioning of such racks within the data center. For example, a rack may include computing equipment as well as a power system, a cooling system, and a cabling system (e.g., for data communication). The rack may include a controller in communication with the computing equipment, the power system, the cooling system, and the cabling system. The rack may also include a rack interface for physically supporting the rack and operatively connecting the systems of the rack to power, cooling, and cabling infrastructure of the data center. The rack interface may receive an autonomous robot for moving the rack within the data center. The controller may control the power system and the cooling system based in part on the autonomous movement of the rack.

Abstract: Approaches presented herein provide for receiving liquid coolant from external sources to cold plates of a server or other liquid-cooled computer system. In at least one embodiment, initial standalone manifolds of the server can be forgone or bypassed, with the flow of liquid coolant received to a server at the cold plates. Some components of the server can be provided a source of cooling from the cold plates and other components can be provided the flow of liquid coolant distributed from the cold plates. The flow of liquid coolant can be provided from the cold plates to the some components to as a source of cooling, as well as to a separate manifold to be further distributed. The cold plates can be connected together to provide the appropriate flow of liquid coolant for the server.

Abstract: Systems and methods are directed toward collecting, aggregating, arbitrating, and transmitting data streams from one or more different source locations. An intermediary system may be positioned between a central controller and a variety of source locations to receive data streams from the different source locations along independent data connections. The intermediary system may identify information for transport to a central controller along a separate connection while delaying or otherwise managing the remaining incoming data streams. Upon determining transmission is complete, the intermediary system may then select another data stream for processing while continuing to delay or manage the remaining incoming data streams.

Abstract: Systems, computer program products, and methods are described for resource allocation in a hybrid distributed computational environment. An example system segments a received task into multiple sub-tasks. Upon partitioning the task, each sub-task is assigned to the appropriate computational resource (e.g., CPU, GPU, or QPU), enabling parallel execution of multiple sub-tasks. Both task partitioning and computational resource determination is determined using a machine learning model. Additionally, the machine learning model may continuously monitor the execution of each sub-task by receiving resource utilization information and performance metrics associated with the execution of each sub-task. The resource utilization information and performance metrics may then be used to update the machine learning model.

Abstract: Approaches presented herein provide for the management of power supplied to server trays, such as allowing for power cycling of individual server trays in a server rack powered by a DC busbar. In at least one embodiment, a timer circuit may be triggered by a power cycling command to prevent power from a power source, such as a busbar, to be provided to processing circuitry within a server tray of a server rack, except the timer circuit. The power can be caused be no longer available to the processing circuitry, ending operation of logical operations of the processing circuitry. After a period of time, the timer circuit can generate a signal to cause the power from the power source to be made available to the processing circuitry, allowing for resumed operation. At least a minimum amount of capacitance may be discharged from the processing circuitry during the period of time.

Abstract: Some embodiments described herein provide intelligent movable racks for a data center and a central system for monitoring and directing the positioning of such racks within the data center. For example, a rack may include computing equipment as well as a power system, a cooling system, and a cabling system (e.g., for data communication). The rack may include a controller in communication with the computing equipment, the power system, the cooling system, and the cabling system. The rack may also include a rack interface for physically supporting the rack and operatively connecting the systems of the rack to power, cooling, and cabling infrastructure of the data center. The rack interface may receive an autonomous robot for moving the rack within the data center. The controller may control the power system and the cooling system based in part on the autonomous movement of the rack.

Abstract: Systems, devices, and methods for disaggregating networking components are provided. An example datacenter rack includes a first networking chassis including a first disaggregated server device supported by the first networking chassis. The first disaggregated server device includes a first central processing unit (CPU) and a first graphics processing unit (GPU) coupled with the first CPU configured to perform computing operations associated with the first networking chassis. The example datacenter rack also includes a second networking chassis including a second disaggregated server device supported by the second networking chassis. The second disaggregated server device includes a second CPU and a second GPU coupled with the second CPU configured to perform computing operations associated with the first networking chassis.

Abstract: Systems, devices, and methods for disaggregating networking components are provided. An example networking chassis includes a first disaggregated server device supported by the networking chassis that includes a first central processing unit (CPU) and a first graphics processing unit (GPU) coupled with the first CPU. The networking chassis further includes a first insertable switch module communicably coupled with the first disaggregated server device that includes first switching chipsets and a first fabric management controller coupled with the first switching chipsets. The first insertable switch module at least partially controls data transmission associated with the first disaggregated server device.

Abstract: Systems, devices, and methods for disaggregating networking components are provided. An example networking system includes a first network domain including a first networking chassis. The first networking chassis includes a first disaggregated server device supported by the first networking chassis including a first central processing unit (CPU); and a first graphics processing unit (GPU) coupled with the first CPU. The first CPU and the first GPU are configured to perform one or more computing operations associated with the first networking chassis. The networking system further includes a second network domain comprising a plurality of rack switches operably coupled with at least the first networking chassis.

Abstract: Systems, devices, and methods for disaggregating networking components are provided. An example cable cartridge for network connections includes a housing defining a first portion configured to be coupled with at least a first disaggregated server device supported by a networking chassis. The first disaggregated server device includes a first central processing unit (CPU) and a first graphics processing unit (GPU) coupled with the first CPU. The first CPU and the first GPU are configured to perform one or more computing operations associated with the networking chassis. The housing defines a second portion configured to be coupled with at least a first insertable switch module supported by the networking chassis. The cable cartridge is configured to operably couple the first disaggregated server device and the first insertable switch module.

Abstract: Apparatuses, systems, and methods for communication interfaces of a programmable part. In at least one embodiment, one or more communication interfaces are secured to a top side of a programmable part to provide programmable access to the programmable part after installation on a printed circuit board (PCB), the one or more communication interfaces to be selectively disabled based, at least in part, on a status of the programmable part.

Abstract: Devices, apparatuses, and systems for thermal management in networking and computing systems are provided. An example in-rack thermal management system includes a cooling distribution unit (CDU) that includes a housing that defines a fluid inlet and a fluid outlet, thermal management components supported by the housing, and direct mechanical connections coupled with the fluid inlet and the fluid outlet. The in-rack thermal management system includes a fluid distribution system that includes a primary fluid channel directly coupled with the direct mechanical connection of the fluid inlet, and a secondary fluid channel directly coupled with the direct mechanical connection of the fluid outlet. In operation, the thermal management components dissipate heat of a fluid received by the CDU via the fluid inlet. The direct mechanical connections directly interface with the fluid distribution system to provide fluid communication between the CDU and the fluid distribution system to maximize dimensions of the housing.

Abstract: A secure electronic component assembly is described herein for ensuring the physical integrity of an integrated circuit (IC). The secure electronic component assembly may comprise a printed circuit board (PCB), an integrated circuit (IC) mounted on the PCB, and an underfill material disposed between the IC and the PCB. The underfill material comprises a detection agent that is configured to change a state of the IC in response to exposure to an external environment, wherein the change in the state of the IC is indicative of a tamper condition.

Abstract: Methods are described herein for manufacturing multi-component objects using artificial intelligence. The present invention may be directed to a method that includes determining an actual value of a first attribute of a first component of an object and determining, using a machine learning model and based on the actual value of the first attribute, an optimized value for a second attribute of a second component that is functionally interrelated to the first component in the object. The method may include selecting, from a plurality of second components each having a value for the second attribute within a tolerance range, a second component having the optimized value for the second attribute. The method may further include manufacturing the object using the first component and the selected second component.