Abstract: A computer-implemented method enables rack-level predictive power capping and power budget allocation to processing nodes in a rack-based IHS. A rack-level management controller receives node-level power-usage data and settings from several block controllers, including current power consumption and an initial power budget for each node. A power consumption profile is generated based on the power-usage data for each node. A total available system power of the IHS is identified. A system power cap is determined based on the power consumption profiles and the total available system power. A current power budget is determined for each node based on an analysis of at least one of the power consumption profile, the initial power budget, the current power consumption, the system power cap, and the total available system power. A power subsystem regulates power budgeted and supplied to each node based on the power consumption profiles and the system power cap.

Abstract: A computer-implemented method enables rack-level predictive power capping and power budget allocation to processing nodes in a rack-based IHS. A rack-level management controller receives node-level power-usage data and settings from several block controllers, including current power consumption and an initial power budget for each node. A power consumption profile is generated based on the power-usage data for each node. A total available system power of the IHS is identified. A system power cap is determined based on the power consumption profiles and the total available system power. A current power budget is determined for each node based on an analysis of at least one of the power consumption profile, the initial power budget, the current power consumption, the system power cap, and the total available system power. A power subsystem regulates power budgeted and supplied to each node based on the power consumption profiles and the system power cap.

Abstract: A computer-implemented method enables rack-level predictive power capping and power budget allocation to processing nodes in a rack-based IHS. A rack-level management controller receives node-level power-usage data and settings from several block controllers, including current power consumption and an initial power budget for each node. A power consumption profile is generated based on the power-usage data for each node. A total available system power of the IHS is identified. A system power cap is determined based on the power consumption profiles and the total available system power. A current power budget is determined for each node based on an analysis of at least one of the power consumption profile, the initial power budget, the current power consumption, the system power cap, and the total available system power. A power subsystem regulates power budgeted and supplied to each node based on the power consumption profiles and the system power cap.

Abstract: DCMI functionality is extended to platforms of a datacenter by integrating a management controller in each of plural platforms and interfacing the management controllers with a management server through a network. End users interface with platforms of the datacenter using DCMI protocol communications. The management server supports communication with management controllers by receiving DCMI messages and translating the DCMI messages to a text-based protocol for communications with the management controllers. In one embodiment, the management controllers push sensor information for their associated platforms to a sensor cache of the management server so that the management sensor references the cache to respond to DCMI requests for sensor information.

Abstract: According to one general aspect, a method may include receiving a distributed application installation package. The distributed application installation package may include a distributed application installation file, a support program for the distribute application, and one or more configuration settings. The method may include installing at least the distributed application on a cluster of computing devices, such that the distributed application, when running, executes in a sandbox environment. The method may also include profiling a performance of the distributed application by executing, via the distribute application and within the sandbox environment on the cluster of computing devices, one or more tests. The method may further include generating a performance summary of the distributed application by collecting one or more pieces of profiled data generated during the execution of the one or more tests.

Abstract: A modular, scalable and expandable (MSE) rack-based information handling system (RIHS) includes: a rack assembly having a frame that defines: a front bay chassis with height, depth and width dimensions that enable insertion of a plurality of different sizes of IT gear; and a rear bay that accommodates power and cooling components to support operation of the different sizes of IT gear. The power and cooling for the IT gear are provided from the rear bay and are separate from and independent of the IT gear installed within the front bay chassis. The rack assembly further includes a power and management chassis in which is inserted a power and management module having power and management components located thereon to provide rack-level power and management. A modular configuration of fan modules are inserted within fan receptacles within the rear bay to provide block level cooling of adjacent blocks of IT gear.

Abstract: A modular, scalable and expandable (MSE) rack-based information handling system (RIHS) includes: a rack assembly having a frame that defines: a front bay chassis with height, depth and width dimensions that enable insertion of a plurality of different sizes of IT gear; and a rear bay that accommodates power and cooling components to support operation of the different sizes of IT gear. The power and cooling for the IT gear are provided from the rear bay and are separate from and independent of the IT gear installed within the front bay chassis. The rack assembly further includes a power and management chassis in which is inserted a power and management module having power and management components located thereon to provide rack-level power and management. A modular configuration of fan modules are inserted within fan receptacles within the rear bay to provide block level cooling of adjacent blocks of IT gear.

Abstract: A computer-implemented method enables rack-level predictive power capping and power budget allocation to processing nodes in a rack-based IHS. A rack-level management controller receives node-level power-usage data and settings from several block controllers, including current power consumption and an initial power budget for each node. A power consumption profile is generated based on the power-usage data for each node. A total available system power of the IHS is identified. A system power cap is determined based on the power consumption profiles and the total available system power. A current power budget is determined for each node based on an analysis of at least one of the power consumption profile, the initial power budget, the current power consumption, the system power cap, and the total available system power. A power subsystem regulates power budgeted and supplied to each node based on the power consumption profiles and the system power cap.

Abstract: A thermal state within an information handling system enclosure is managed within predetermined constraints by estimating thermal energy introduced to the enclosure by power dissipation to electronic components and thermal energy removed from the enclosure by a cooling airflow generated by a fan. A desired bulk temperature of a cooling airflow is attained at a predetermined position in an enclosure by selecting a fan speed and power allocation to the components that conserves energy within the enclosure at a predetermined thermal state.

Abstract: A modular rack-level server and storage framework is disclosed. The modular rack system includes a plurality of chassis placed in one or more racks and a plurality of sleds placed in each chassis. Each sled includes an information handling system, a shared fan module, a shared power module, and a shared management module. The shared fan module cools the plurality of sleds in each chassis and the shared power module supplies power to one or more sleds in one or more chassis. The shared management module manages the operation of the plurality of chassis.

Abstract: A thermal state within an information handling system enclosure is managed within predetermined constraints by estimating thermal energy introduced to the enclosure by power dissipation to electronic components and thermal energy removed from the enclosure by a cooling airflow generated by a fan. A desired bulk temperature of a cooling airflow is attained at a predetermined position in an enclosure by selecting a fan speed and power allocation to the components that conserves energy within the enclosure at a predetermined thermal state.

Abstract: DCMI functionality is extended to platforms of a datacenter by integrating a management controller in each of plural platforms and interfacing the management controllers with a management server through a network. End users interface with platforms of the datacenter using DCMI protocol communications. The management server supports communication with management controllers by receiving DCMI messages and translating the DCMI messages to a text-based protocol for communications with the management controllers. In one embodiment, the management controllers push sensor information for their associated platforms to a sensor cache of the management server so that the management sensor references the cache to respond to DCMI requests for sensor information.

Abstract: An information handling system tray component is selected for a depth to fit into chassis support components to provide processing resources in a space having different depths. An end user selects a chassis component having a depth that fits a data center and then installs tray components into the chassis component by selecting the tray component depths to fit in that of the chassis component. The tray component supports different processing components depending upon the selected depth so that information handling system features are adapted to chassis depth while using a common infrastructure component.

Abstract: A modular rack-level server and storage framework is disclosed. The modular rack system includes a plurality of chassis placed in one or more racks and a plurality of sleds placed in each chassis. Each sled includes an information handling system, a shared fan module, a shared power module, and a shared management module. The shared fan module cools the plurality of sleds in each chassis and the shared power module supplies power to one or more sleds in one or more chassis. The shared management module manages the operation of the plurality of chassis.