Abstract: A redundancy shut-off system for a datacenter liquid cooling system is disclosed. The redundancy shut-off system has a first ball valve located above a datacenter platform and coupling between a row manifold of a secondary cooling loop and a rack manifold of a rack, where the first ball valve provides redundancy to a second ball valve located below the datacenter platform.

Abstract: Systems and methods for evaluating cooling characteristics are disclosed. In at least one embodiment, a thermal test vehicle can be used to simulate a thermal performance of a computing unit.

Abstract: A system comprising an adapter plate to couple a plurality of different types of cooling manifolds to one or more racks in a datacenter is disclosed. Additionally, a system comprising an adapter plate to adaptively couple a cooling manifold to a plurality of different types of server racks is disclosed.

Abstract: An adapter plate and a fastening system for fastening a manifold to a rack in a datacenter is disclosed. The adapter plate is associated with the manifold and has holes to receive buttons in configurable positions. The configurable positions enable the buttons to mate with keyholes of a bracket of the rack in order to fasten the manifold to the bracket.

Abstract: Systems and methods for cooling a datacenter are disclosed. In at least one embodiment, a plurality of in-rack coolant distribution units (IRCDUs) include a first IRCDU and a second IRCDU that are interchangeable within a rack depending on a type of coolant to be provided to a rack from a coolant distribution unit (CDU), so that a first IRCDU that is calibrated to a first coolant can distribute a first coolant and a second IRCDU that is calibrated to a second coolant can distribute a second coolant to a rack manifold of a rack.

Abstract: Configurations for exhaust baffles are disclosed. In at least one embodiment, one or more baffles direct an outlet air flow from a heat exchanger.

Abstract: Techniques for optimizing power and computational density of data centers are described. According to various embodiments, a benchmark test is performed by a computer data center system. Thereafter, transaction information and power consumption information associated with the performance of the benchmark test are accessed. An efficiency metric value is then generated based on the transaction information and the power consumption information. In some implementations, the efficiency metric value indicates a number of transactions executed via the computer data center system during a specific time period per unit of power consumed in executing the transactions during the specific time period. The generated efficiency metric value is then compared to a target threshold value. Thereafter, a performance summary report indicating the generated efficiency metric value, and indicating a result of the comparison of the generated efficiency metric value to the target value, is generated.

Abstract: Systems and methods for evaluating cooling characteristics are disclosed. In at least one embodiment, a thermal test vehicle can be used to simulate a thermal performance of a computing unit.

Abstract: Systems and methods for cooling a datacenter are disclosed. In at least one embodiment, an integrated power and coolant distribution unit (PCDU) comprises control logic to cause at least one power controller to provide a power response or to cause at least one flow controller to provide a coolant response from the PCDU upon a determined change in a power state or coolant state.

Abstract: A redundancy shut-off system for a datacenter liquid cooling system is disclosed. The redundancy shut-off system has a first ball valve located above a datacenter platform and coupling between a row manifold of a secondary cooling loop and a rack manifold of a rack, where the first ball valve provides redundancy to a second ball valve located below the datacenter platform.

Abstract: An adapter plate and a fastening system for fastening a manifold to a rack in a datacenter is disclosed. The adapter plate is associated with the manifold and has holes to receive buttons in configurable positions. The configurable positions enable the buttons to mate with keyholes of a bracket of the rack in order to fasten the manifold to the bracket.

Abstract: Techniques for optimizing power and computational density of data centers are described. According to various embodiments, a benchmark test is performed by a computer data center system. Thereafter, transaction information and power consumption information associated with the performance of the benchmark test are accessed. A service efficiency metric value is then generated based on the transaction information and the power consumption information, the service efficiency metric value indicating a number of transactions executed via the computer data center system during a specific time period per unit of power consumed in executing the transactions during the specific time period. The generated service efficiency metric value is then compared to a target threshold value. Thereafter, a performance summary report indicating the generated service efficiency metric value, and indicating a result of the comparison of the generated service efficiency metric value to the target value, is generated.

Abstract: Techniques for optimizing power and computational density of data centers are described. According to various embodiments, a benchmark test is performed by a computer data center system. Thereafter, transaction information and power consumption information associated with the performance of the benchmark test are accessed. A service efficiency metric value is then generated based on the transaction information and the power consumption information, the service efficiency metric value indicating a number of transactions executed via the computer data center system during a specific time period per unit of power consumed in executing the transactions during the specific time period. The generated service efficiency metric value is then compared to a target threshold value. Thereafter, a performance summary report indicating the generated service efficiency metric value, and indicating a result of the comparison of the generated service efficiency metric value to the target value, is generated.

Abstract: Techniques for optimizing power and computational density of data centers are described. According to various embodiments, a benchmark test is performed by a computer data center system. Thereafter, transaction information and power consumption information associated with the performance of the benchmark test are accessed. A service efficiency metric value is then generated based on the transaction information and the power consumption information, the service efficiency metric value indicating a number of transactions executed via the computer data center system during a specific time period per unit of power consumed in executing the transactions during the specific time period. The generated service efficiency metric value is then compared to a target threshold value. Thereafter, a performance summary report indicating the generated service efficiency metric value, and indicating a result of the comparison of the generated service efficiency metric value to the target value, is generated.

Abstract: Techniques for optimizing power and computational density of data centers are described. According to various embodiments, a benchmark test is performed by a computer data center system. Thereafter, transaction information and power consumption information associated with the performance of the benchmark test are accessed. A service efficiency metric value is then generated based on the transaction information and the power consumption information, the service efficiency metric value indicating a number of transactions executed via the computer data center system during a specific time period per unit of power consumed in executing the transactions during the specific time period. The generated service efficiency metric value is then compared to a target threshold value. Thereafter, a performance summary report indicating the generated service efficiency metric value, and indicating a result of the comparison of the generated service efficiency metric value to the target value, is generated.

Abstract: Techniques for optimizing power and computational density of data centers are described. According to various embodiments, a benchmark test is performed by a computer data center system. Thereafter, transaction information and power consumption information associated with the performance of the benchmark test are accessed. A service efficiency metric value is then generated based on the transaction information and the power consumption information, the service efficiency metric value indicating a number of transactions executed via the computer data center system during a specific time period per unit of power consumed in executing the transactions during the specific time period. The generated service efficiency metric value is then compared to a target threshold value. Thereafter, a performance summary report indicating the generated service efficiency metric value, and indicating a result of the comparison of the generated service efficiency metric value to the target value, is generated.

Abstract: Techniques for optimizing power and computational density of data centers are described. According to various embodiments, a benchmark test is performed by a computer data center system. Thereafter, transaction information and power consumption information associated with the performance of the benchmark test are accessed. A service efficiency metric value is then generated based on the transaction information and the power consumption information, the service efficiency metric value indicating a number of transactions executed via the computer data center system during a specific time period per unit of power consumed in executing the transactions during the specific time period. The generated service efficiency metric value is then compared to a target threshold value. Thereafter, a performance summary report indicating the generated service efficiency metric value, and indicating a result of the comparison of the generated service efficiency metric value to the target value, is generated.

Abstract: Techniques for optimizing power and computational density of data centers are described. According to various embodiments, a benchmark test is performed by a computer data center system. Thereafter, transaction information and power consumption information associated with the performance of the benchmark test are accessed. A service efficiency metric value is then generated based on the transaction information and the power consumption information, the service efficiency metric value indicating a number of transactions executed via the computer data center system during a specific time period per unit of power consumed in executing the transactions during the specific time period. The generated service efficiency metric value is then compared to a target threshold value. Thereafter, a performance summary report indicating the generated service efficiency metric value, and indicating a result of the comparison of the generated service efficiency metric value to the target value, is generated.

Abstract: Techniques for optimizing power and computational density of data centers are described. According to various embodiments, a benchmark test is performed by a computer data center system. Thereafter, transaction information and power consumption information associated with the performance of the benchmark test are accessed. A service efficiency metric value is then generated based on the transaction information and the power consumption information, the service efficiency metric value indicating a number of transactions executed via the computer data center system during a specific time period per unit of power consumed in executing the transactions during the specific time period. The generated service efficiency metric value is then compared to a target threshold value. Thereafter, a performance summary report indicating the generated service efficiency metric value, and indicating a result of the comparison of the generated service efficiency metric value to the target value, is generated.

Abstract: Techniques for optimizing power and computational density of data centers are described. According to various embodiments, a benchmark test is performed by a computer data center system. Thereafter, transaction information and power consumption information associated with the performance of the benchmark test are accessed. A service efficiency metric value is then generated based on the transaction information and the power consumption information, the service efficiency metric value indicating a number of transactions executed via the computer data center system during a specific time period per unit of power consumed in executing the transactions during the specific time period. The generated service efficiency metric value is then compared to a target threshold value. Thereafter, a performance summary report indicating the generated service efficiency metric value, and indicating a result of the comparison of the generated service efficiency metric value to the target value, is generated.